Global Longitudinal Health Monitoring and Blood Sample Collection Study to Promote Early-stage Disease Detection and Personalized/Precision Care Using Innovative Research Platforms

Overview

The investigators propose a prospective, longitudinal, observational study to improve health assessment by analyzing blood plasma molecular patterns in each individual over time using artificial intelligence (AI) to identify key measurements for early detection of NCDs. It will develop personalized reference ranges and screening methods, laying the foundation for population-based early detection. This study focus on collecting health data and biospecimen samples to understand early molecular changes linked to disease.

Background: According to the WHO, non-communicable diseases (NCDs) cause about 70% of global deaths-over 43 million in 2021- with up to 90% in high-income countries. These diseases are linked to risk factors such as unhealthy diets, inactivity, tobacco, and alcohol, leading to long-term health issues and economic burdens. Current screening methods mainly detect clinical signs but lack early sensitivity. Emerging approaches focus on biomarkers, advanced technologies, and machine learning to improve early detection and personalized prevention, aiming to reduce NCD impact and improve health outcomes. An individual's blood parameters are usually stable and reflect their unique physiology. Comparing current results to personal baseline ranges is more sensitive for detecting health issues than using general population standards. This personalized approach aims to identify early molecular changes indicating potential NCDs. This study builds upon the ongoing Health for Hungary (H4H) (https://www.h4h.hu/en/) project conducted by the Center for Molecular Fingerprinting, a non-profit research institution in Hungary led by 2023 Nobel Laureate in Physics, Prof. Ferenc Krausz (https://www.physics.hku.hk/people/academic\_staff/teaching\_staff/f\_krausz/). Aim: The primary scientific goal of the project is to quantitatively parametrize health in terms of time series of integrated molecular parameters and molecular pattern recognition from human blood plasma, and leverage AI to discover the minimum set of molecular data of blood that reliably assess and predict any changes in human health. The overarching aim of the study is to establish the technological and economic basis for a population-based health screening for major NCDs. Study Design and overview: The study is a prospective, longitudinal, observational study with no therapeutic intervention, focusing on collecting health data and samples to understand early molecular changes linked to disease. A total of 15,000 participants will be recruited. This study aims to recruit participants in a 1 to 1 ratio across the two groups (Low-risk arm and High-risk arm). Participants, including both sexes aged 40-70 years at enrollment, will be recruited and assigned to one of two distinct cohorts based on their NCD risk profile: 1. Low-risk arm: a cohort of 7,500 participants with the absence of modifiable cardiovascular risk factors, who are at low risk of contracting selected NCDs, 2. High-risk arm: a cohort of 7,500 participants with the presence of cardiovascular risk factors, who are at high risk of contracting selected NCDs. Participants are to be clinically followed up for 10 years, and followed by continuous regular outcome ascertainment for an additional 10 years only through data-linkage. The study begins with a baseline visit on Visit 1 to determine the participants' eligibility for the study and signing of informed consent form. Participants will be completed a detailed 30-minute health questionnaire, body measurements, undergo vital signs and resting ECG assessment, and provide fasting blood for molecular fingerprinting measurement and routine laboratory testing including Complete blood counts, Liver function tests, Kidney function tests, Metabolic and lipid panels, Thyroid function tests, Inflammatory markers and Tumor markers. Urine samples will be tested for urinalysis and microalbuminuria. Eligibility will be confirmed after a medical review of the participants' electronic health record (if applicable) and the collected data. Three additional monthly baseline visits occur during Months 2-4, involving fasting blood collection, a short health update questionnaire, directed physical exam, and reporting of any adverse events. Coronary artery calcium score test (CAC) and Low-dose chest CT scan (LDCT) (aged 50 or more and are with ≥ 20 pack years at visit 1, i.e. high risk group only) will be performed for applicable high-risk participants as part of extended medical check-up at visit 2-4. Between visit 2 and visit 4, CAC and LDCT should be performed once only. Finally, a Comprehensive Medical Check-Up will be arranged at Years 5 (Visit 13) and 10 (Visit 23) for both high-risk and low-risk participants, while high-risk participants will undergo repeated CAC test and LDCT scan. Over the following 10 years, participants will be attended half-yearly follow-up visits that include a short questionnaire, body measurements, vital signs, ECG, fasting blood and urine collection, and reporting of new health conditions. After Year 10, no further clinic visits are planned, but the study team will continue annual health record review for another 10 years and may contact participants or their next of kin for additional health information. Primary outcome measures: Identification of molecular signatures associated with specific risk profiles and disease trajectories Main data analysis: Full Analysis Set and Per-Protocol Set (PPS) approach Potential significance: The findings will help to establish the technological and economic basis for a population-based health screening for major NCDs