Study on Aging and Cognitive Impairment in China

Overview

Background: By the end of 2022, China had about 280 million people aged 60 and older, making up 19.8% of the population. This number is projected to exceed 300 million by the end of the 14th Five-Year Plan and 400 million by 2035, which would be over 30%. The 20th National Congress emphasized the need for a proactive strategy to tackle aging challenges. Approximately 6.04% of the elderly have dementia, with 3.94% having Alzheimer's disease. This totals around 15 million people with dementia. To address this, the China Cohort Consortium on Aging and Cognitive Impairment Development has been proposed to study health and cognitive changes in different age groups, aiming to support healthy aging policies. Methods: Participants from various age groups (children, youth, middle-aged, elderly) will be recruited from hospitals, schools, and communities using stratified sampling. They will undergo detailed medical examinations focusing on aging, cognitive impairments, and related diseases. A new database will track healthy aging and cognitive impairment development. Content: The study will involve comprehensive medical examinations, including physiological assessments, psychological evaluations, cognitive screenings, daily life assessments, imaging studies, and blood tests, to establish a detailed health and cognitive impairment database. The research will also investigate integrated intervention models in hospital, community, and home settings, develop remote medical management systems, and devise biomarker test kits for aging and cognitive impairments. Furthermore, it will concentrate on non-pharmacological interventions and artificial intelligence systems for the early detection, prevention, and treatment of aging-related conditions. Objectives: The China Cohort Consortium on Aging and Cognitive Impairment Development, commencing with the HAPCAD study, aims to monitor changes across various age groups, evaluate the impact of aging on health and cognitive function, and design targeted interventions. The objective is to enhance health management and services related to aging, establish effective strategies, develop therapeutic drugs, and promote healthy aging.

Research Objectives: Establish detailed medical examinations for population cohorts across different age groups, including physiological checks, psychological assessments, cognitive function screenings, evaluations of daily life abilities, imaging, and blood tests, to build a comprehensive health and mental impairments database. Develop artificial intelligence systems for early warnings related to aging-related diseases and create prevention and treatment strategies. Focus on advancing health management, interventions, research, and services related to healthy aging and aging-related diseases, and develop effective intervention strategies and therapeutic drugs to promote healthy aging. Research Content: 1. Screening and Tracking: Implement a long-term cohort study on healthy aging and cognitive impairment to understand changes in physiological, psychological, mental, and daily life abilities across different age groups. Analyze the effects of genetic, environmental, and lifestyle factors on healthy aging and cognitive impairments. Based on identified risk factors, develop personalized lifestyle interventions and management plans. The study will include 20,000 participants. 2. Omics Approaches: Use genomics, transcriptomics, proteomics, and metabolomics to identify biomarkers associated with healthy aging, cognitive impairments, and other aging-related diseases. This will support further primary research in these areas. Research Methods and Technical Roadmap: 1. Questionnaire Survey: Collect demographic information (age, gender, height, weight, education, occupation, smoking, alcohol consumption, dietary habits, medical history, family history, medication history, etc.) and conduct various scale assessments. Specific scales will include Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) Background Version, memory and digit span tests, Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), PHQ-9 Depression Screening Scale, HIS Ischemia Scale, Neuropsychiatric Inventory (NPI), Pittsburgh Sleep Quality Index (PSQI), International Physical Activity Questionnaire (IPAQ), Activities of Daily Living (ADL), Clinician's Interview-Based Impression of Change Plus Caregiver Input (CIBIC-PLUS), Clinical Dementia Rating (CDR) scale, and Epidemic Protective Behavior Scale. 2. Clinical Laboratory Index Collection: Perform blood tests (complete blood count, biochemical tests, glucose, glycated hemoglobin, lipid profile, folic acid, vitamin B, homocysteine, thyroid function, C-reactive protein), urinalysis, stool tests, and measure biomarkers (ApoE, T-tau, NFL, GFAP, UCHL1, pTau-181, pTau-217, Aβ40, Aβ42, etc.). 3. Clinical Examination Index Collection: Conduct brain MRI, Transcranial Doppler (TCD), carotid artery and vertebral artery ultrasound, echocardiogram, lower limb vascular ultrasound, ambulatory blood pressure monitoring, fundus photography, CT scans, and review pathological reports. 4. Sample Collection: Collect blood, cerebrospinal fluid, brain tissue, stool, urine, and saliva as needed for clinical diagnostics. Additional samples (20 ml blood, 10 ml urine, 30 ml stool, 20 ml saliva) will be collected, processed, and analyzed for genomics, transcriptomics, proteomics, and metabolomics to identify specific biomarkers. 4.1. Genomics: Use the Illumina platform for whole-genome sequencing (WGS) to identify genetic variations and conduct genotype diversity, evolution analysis, and disease screening. Perform whole-genome bisulfite sequencing (WGBS) to study DNA methylation, which supports research on genome-wide methylation modifications relevant to aging and diseases. 4.2. Transcriptomics: Utilize the Illumina platform for next-generation sequencing to analyze coding and non-coding RNAs. Employ the 10x Chromium Single Cell Gene Expression Solution platform for single-cell gene expression profiling, enabling detailed analysis of cell populations and creating single-cell expression atlases. 4.3. Proteomics and Metabolomics: Study protein composition and activity patterns using proteomics and explore small molecule metabolites using metabolomics. Integrate data from both approaches to identify differential proteins and metabolites and describe molecular regulatory mechanisms. Follow-Up and Tracking: Track and follow up with enrolled participants. Experimental Methods: Employ traditional and advanced statistical methods, including t-tests, non-parametric tests, chi-square tests, logistic regression, Cox proportional hazards models, artificial neural networks, and Bayesian models. Analyze data to identify biomarkers for disease prediction, explore disease mechanisms, and guide treatment strategies. Utilize samples for scientific analysis, molecular experiments, and drug development. Key Technologies and Descriptions: Sample Processing: Use centrifuges, slicers, pipettes, and DNA/RNA extraction instruments. Following standardized procedures, store samples in low-temperature equipment, including refrigerators, freezers, and liquid nitrogen tanks. Simoa Detection Technology: Utilize Simoa for single-molecule detection with high sensitivity, using capture antibody binding sites on magnetic beads and detecting signals using CCD cameras. This technology allows for precise measurement of protein concentrations. Annual Research Plan: Recruit volunteers from hospitals of all age groups for comprehensive physical examinations, aiming to establish a detailed human growth and aging map.