Xuan Wu Hospital of Capital Medical University
Beijing, Beijing Municipality, 100053, China
Location status: Recruiting
NCT Number: NCT05697588
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.
Interested in participating?
Request Info50 year–85 year
All sexes
Observational
Beijing, Beijing Municipality, 100053, China
Location status: Recruiting
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.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 5 years
Assess statistically significant difference in score between MCI-P and MCI-S using the neuropsychological scales CDR. CDR, a multidimensional scale for dementia severity, which scored 0-3, with higher scores indicating worse functioning.
Time frame: 5 years
Assess statistically significant difference in score between MCI-P and MCI-S using the neuropsychological scales MMSE. MMSE scores range from 0-30, with higher scores representing better cognitive function.
Time frame: 5 years
Assess statistically significant difference in score between MCI-P and MCI-S using the neuropsychological scales MoCA. MoCA scores range from 0-30, with higher scores representing better cognitive function.
Time frame: 5 years
Assess statistically significant difference in score between MCI-P and MCI-S using the neuropsychological scales ADAS-cog. ADAS-cog scores range from 0-70, with higher scores indicating better global cognitive function.
Time frame: 5 years
Assess statistically significant difference in score between MCI-P and MCI-S using the neuropsychological scales like WHO-UCLA AVLT. WHO-UCLA AVLT scores depend on the number of correct words, which ranges from 0-15, with higher scores representing better memory function.
Time frame: 5 years
Assess statistically significant difference in score between MCI-P and MCI-S using the neuropsychological scales like BNT. BNT scores range from 0-30, with higher scores representing better language function.
Time frame: 5 years
Assess statistically significant difference in score between MCI-P and MCI-S using the neuropsychological scales like NPI. Patient assessment grading scores range from 0-144 in NPI, and caregivers distress grading scores range from 0-60, with 0 representing the best.
Time frame: 5 years
Assess statistically significant difference between in score MCI-P and MCI-S using the neuropsychological scales like ADCS-ADL. ADCS-ADL scores range from 0-54, with higher scores indicating better completion ability.
Time frame: 5 years
Assess statistic difference in protein content between MCI-P and MCI-S using CSF and blood samples through proteomics DIA technology analysis.
Time frame: 5 years
Assess statistically significant difference in small molecule metabolite between MCI-P and MCI-S using stool and urine through untargeted metabolomics (LC-MS) analysis.
Time frame: 5 years
Assess statistically significant difference in transcription between MCI-P and MCI-S using stool samples through DNA high-throughput sequencing analysis.
Time frame: 5 years
Assess statistically significant difference in content between MCI-P and MCI-S using CSF and blood samples, through detecting the classical AD marker content.
Time frame: 5 years
Time frame: 5 years
Time frame: 5 years
Time frame: 5 years
Time frame: 5 years
Time frame: 5 years
Time frame: 5 years
Time frame: 5 years
Time frame: 5 years
Contact information is provided by the study sponsor or research team.
Cuibai Wei,Clinical Professor
Other
Studies on Biomarkers for Mild Cognitive Impairment Conversion to Dementia
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