Biomarker-Integrated Digital Guidance for Early Alzheimer's Detection (BRIDGE-AD): A Nationwide Multicenter Study

Biomarker-Integrated Digital Guidance for Early Alzheimer's Detection (BRIDGE-AD): A Nationwide Multicenter Study

The investigators propose a stepwise screening approach. The first step involves rapid digital pre-screening of cognitive function through three components: the SCD-9 questionnaire to capture subjective cognitive complaints, a digital cognitive assessment to evaluate objective performance, and a predictive model to estimate future dementia risk in cognitively normal individuals. The second step confirms the presence of AD pathology using blood-based biomarkers, with a head-to-head comparison of multiple novel candidates to identify those with the greatest diagnostic utility.

Background: Cognitive impairment represents a spectrum of conditions affecting memory, reasoning, and daily functioning, with Alzheimer's disease (AD) constituting 60-80% of dementia cases globally. The worldwide burden of AD has reached 56.9 million cases, with projections indicating this will escalate dramatically due to population aging, particularly in low- and middle-income countries which will bear 65% of the economic burden by 2050.

The progression of AD typically involves a prolonged preclinical phase lasting 15-20 years before symptom onset. This extended window, coupled with the mild cognitive impairment stage, presents critical opportunities for early intervention. Contemporary diagnostic paradigms have shifted from symptom-based to pathology-driven criteria, enabling detection through biomarkers during asymptomatic phases. Community settings serve as ideal platforms for population-wide monitoring, where systematic screening combined with interventions like lifestyle modifications and cognitive training may also delay disease progression.

Current cognitive impairment screening systems face considerable challenges in terms of accuracy, efficiency, and scalability. Standard neuropsychological assessments are constrained by practice effects, subjective scoring, limited sensitivity to early cognitive changes, and the need for trained professionals. Emerging digital tools can improve testing efficiency and maintain high accuracy, offering benefits such as automated scoring and reduced reliance on specialized personnel. Meanwhile, predicting the future risk of dementia in cognitively normal individuals could enable personalized monitoring strategies. In the era of disease-modifying therapies, early detection of AD pathology is essential for initiating timely interventions. Therefore, there is an urgent need for accessible, scalable, and cost-effective screening approaches that can detect both cognitive symptoms and AD pathology, particularly in aging populations and resource-limited settings where the burden of dementia is growing most rapidly.

Our research proposes a stepwise screening approach. The first step involves rapid digital pre-screening of cognitive function through three components: the SCD-9 questionnaire to capture subjective cognitive complaints, a digital cognitive assessment to evaluate objective performance, and a predictive model to estimate future dementia risk in cognitively normal individuals. The second step confirms the presence of AD pathology using blood-based biomarkers, with a head-to-head comparison of multiple novel candidates to identify those with the greatest diagnostic utility.

Research Objective: Develop a screening and diagnostic pathway integrating digital cognitive tools and blood biomarkers for early detection of AD-related cognitive impairment in community populations.

Innovations: (1) Enhance screening efficiency via digital cognitive assessments. (2) Improve diagnostic accuracy by combining blood biomarkers. (3) Establish a community-based operational model tailored to China's primary healthcare system, offering a scalable reference for dementia action plans in developing countries.

Study Design: A nationwide, multicenter study. Study Setting: Nationwide multicenter, encompassing Beijing, Shenzhen (Guangdong Province), Haikou (Hainan Province), Shenyang (Liaoning Province), Yichun (Jiangxi Province), and Ningxia (Ningxia Hui Autonomous Region).

Sample Size: A total of 6,000 participants. The sample sizes will be allocated proportionally, based on the population aged 50 and above in each multicenter community.

Study Population: Community residents aged 50 and above who have resided in the community for over one-year, self-report no cognitive impairment disorder or use of anti-dementia medications, and are capable of communicating in Chinese. Participants with a self-reported or clinically confirmed diagnosis of severe psychiatric disorders, such as bipolar disorder or schizophrenia, as well as those with medical conditions that impair their ability to complete cognitive assessments, were excluded.

Screening Strategy:

1. Part 1: The first screening step includes the SCD-9 questionnaire (a brief self-assessment of cognitive decline), the PCAT digital cognitive test (comprising face-name memory and symbol matching tasks), and a dementia risk prediction model based on validated models identified through a systematic review.

   Gold standard of cognitive impairment: Clinical Dementia Rating (CDR), evaluated by a qualified physician.

2. Part 2: The second diagnostic step targets AD pathology using multiple blood-based biomarkers, including conventional markers (p-tau217, p-tau181, Aβ42/40) and emerging microRNA candidates. Various assay platforms, such as Simoa and CLEIA, will be utilized for biomarker quantification.

Gold standard of AD pathology: amyloid PET scan.

Outcome Measures:

(1) Primary outcome: Sensitivity and specificity of the AD-related cognitive impairment screening and diagnosis program. (2) Secondary outcome: program completion rate, time to completion, community feasibility, compliance, and health-economic evaluation (cost per participant) for screening and diagnosis.

Statistical Methods: Statistical analysis will be conducted using the screening research analysis framework and health economics calculation theory, with P<0.05 considered statistically significant.

Inclusion Criteria:

1. adults aged 50 and above;
2. living in community for at least one year and having established medical records;
3. denying a history of cognitive disorders (mild cognitive impairment, dementia, Alzheimer's disease, etc.) and the use of anti-dementia drugs (cholinesterase inhibitors or memantine, etc.);
4. agreeing to participate in the study;
5. individual or their relatives can communicate normally in Chinese.
6. high-risk groups for dementia（including:1. Complaints of cognitive decline and/or statements by the informant;2. History of AD in first-degree relatives;3. Known ApoE e4 carrier.）

Exclusion Criteria:

1. Self-reporting or confirmation through inquiry indicates the presence of severe mental disorders, such as bipolar disorder or schizophrenia, etc.
2. Having a disease that makes it impossible to complete the cognitive assessment.