Biomarkers Clinical Trial
Official title:
Studies on Biomarkers for Mild Cognitive Impairment Conversion to Dementia
Verified date | January 2023 |
Source | Xuanwu Hospital, Beijing |
Contact | Cuibai Wei |
Phone | 83198319 |
weicb[@]xwhosp.org | |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
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.
Status | Not yet recruiting |
Enrollment | 900 |
Est. completion date | February 28, 2028 |
Est. primary completion date | February 28, 2028 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 50 Years to 85 Years |
Eligibility | Inclusion Criteria: - Male or female patients aged =50 and =85 years; - Meet the diagnostic criteria for dementia or MCI; ? Neuropsychological score: MMSE 15-28 points, CDR=1 point; ? 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; ? There are contraindications to nuclear magnetic resonance; - There is mental and neurodevelopmental delay; ? refuse to draw blood; ? Refuse to sign the informed consent. |
Country | Name | City | State |
---|---|---|---|
China | Xuan Wu Hospital of Capital Medical University | Beijing | Beijing |
Lead Sponsor | Collaborator |
---|---|
weicuibai | Beihang University, Chinese PLA General Hospital, Chongqing Medical University, First Hospital of Shijiazhuang City, Jilin University, The Affiliated Zhongshan Hospital of Dalian University, Tianjin Huanhu Hospital |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Rate of change in global cognition as measured by Clinical Dementia Rating (CDR). | 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. | 5 years | |
Primary | Rate of change in global cognition as measured by Mini-Mental State Examination (MMSE). | 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. | 5 years | |
Primary | Rate of change in global cognition as measured by Montreal Cognitive Assessment (MoCA). | 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. | 5 years | |
Primary | Rate of change in the severity of cognitive impairment as assessed by Alzheimer's Disease Assessment Scale-Cognitive section (ADAS-cog). | 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. | 5 years | |
Primary | 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). | 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. | 5 years | |
Primary | Rate of change in language function as assessed by Boston Naming Test (BNT). | 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. | 5 years | |
Primary | Rate of change in psychobehavioral symptoms as assessed by Neuropsychiatric Inventory (NPI). | 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. | 5 years | |
Primary | Rate of change in activities of daily living as assessed by Alzheimer's Disease Cooperative Study-Activity of Daily Living (ADCS-ADL). | 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. | 5 years | |
Secondary | Rate of change in differential protein content as assessed by CSF and blood samples. | Assess statistic difference in protein content between MCI-P and MCI-S using CSF and blood samples through proteomics DIA technology analysis. | 5 years | |
Secondary | Rate of change in small molecule metabolite as assessed by stool and urine. | Assess statistically significant difference in small molecule metabolite between MCI-P and MCI-S using stool and urine through untargeted metabolomics (LC-MS) analysis. | 5 years | |
Secondary | Rate of change in metagenomes as assessed by stool samples. | Assess statistically significant difference in transcription between MCI-P and MCI-S using stool samples through DNA high-throughput sequencing analysis. | 5 years | |
Secondary | Rate of change in classical AD protein biomarkers as assessed by CSF and blood samples. | Assess statistically significant difference in content between MCI-P and MCI-S using CSF and blood samples, through detecting the classical AD marker content. | 5 years | |
Secondary | Rate of change in sleep apnea hypopnea as assessed by Standard night Polysomnography. | 5 years | ||
Secondary | Rate of change in brain resting state activity as assessed by Resting state electroencephalogram (EEG). | 5 years | ||
Secondary | Rate of change in brain stem damage as assessed by Evoked potentials (EPs). | 5 years | ||
Secondary | Rates of change in brain structure using brain structure magnetic resonance imaging (sMRI). | 5 years | ||
Secondary | Rates of change in brain function characteristics using brain functional MRI (fMRI). | 5 years | ||
Secondary | Rates of change in white matter fiber bundle using Diffusion tensor image (DTI). | 5 years | ||
Secondary | Rates of change in glucose metabolism as measured by 18F-FDG-PET. | 5 years | ||
Secondary | Rates of change in amyloid deposition as measured by amyloid-PET | 5 years | ||
Secondary | Rates of change in tau deposition as measured by tau-PET. | 5 years |
Status | Clinical Trial | Phase | |
---|---|---|---|
Active, not recruiting |
NCT05095324 -
The Biomarker Prediction Model of Septic Risk in Infected Patients
|
||
Recruiting |
NCT05548933 -
Effects of Non-surgical Periodontal Therapy on Severe Periodontitis and Hyperlipidemia
|
||
Active, not recruiting |
NCT03926572 -
Acute Decompensation of Pulmonary Hypertension
|
N/A | |
Recruiting |
NCT05372159 -
Vanderbilt Memory and Aging Project
|
||
Completed |
NCT03173586 -
Sugar Sweetened Beverage Intake and Biomarkers of Cardiometabolic Risk in US Women
|
N/A | |
Completed |
NCT04554628 -
Early Prediction of Acute Kidney Injury Among Patients Admitted to Surgical ICU
|
N/A | |
Terminated |
NCT03250312 -
The Effects of OMT on the Expression Patterns of Immune Cell Biomarkers
|
N/A | |
Recruiting |
NCT04666766 -
Detecting Traumatic Intracranial Hemorrhage With Microwaves and Biomarkers
|
N/A | |
Completed |
NCT04573543 -
The Role of Immune Semaphorins in NAFLD
|
||
Completed |
NCT03193671 -
Evaluation and Implementation of New Biomarkers and Algorithms for Diagnosis of Ovarian Cysts/Tumors in the Pelvis
|
N/A | |
Recruiting |
NCT06047132 -
PREDICTIVE ABILITY OF A PANEL OF BIOMARKERS IN SALIVA IN HEALTHY AND PERIODONTALLY AFFECTED SUBJECTS
|
||
Completed |
NCT05361460 -
Patients Experiences of Early Postoperative Cognition
|
||
Recruiting |
NCT05706194 -
Early Neuroprognostication After OHCA
|
||
Recruiting |
NCT05138731 -
Metabolomics Profiling of Coronary Heart Disease
|
||
Recruiting |
NCT06446895 -
Biomarkers of Inflammation and Endothelial Dysfunction in Patients With Myocardial Infarction With Non-obstructive Coronary Arteries
|
||
Not yet recruiting |
NCT04563000 -
Impact of Vitamin C on Biomarkers of Neurologic Injury in Survivors of Cardiac Arrest
|
Phase 2 | |
Completed |
NCT05138692 -
Biomarkers and Outcome 1 and 10-15 Years After Severe Traumatic Brain Injury
|
||
Completed |
NCT02247999 -
Improving Cervical Cancer Screening Among HIV-Infected Women in India
|
||
Active, not recruiting |
NCT02732301 -
Postoperative Gastrointestinal Dysfunction After Cardiac Surgery - Occurrence and Search for Biomarkers
|
||
Not yet recruiting |
NCT03269019 -
Thrombotic Biomarkers to Predict Thrombosis in Heparin-induced Thrombocytopenia
|
N/A |