| Title: | Integrated omics to implore risk, diagnostic, and prognostic factors of cardiovascular disease |
| Lead Institution: | Shantou University Medical College |
| Principal investigator: |
Application 205837
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About
Cardiovascular disease (CVD) is a significant global health challenge, with escalating incidence and mortality rates. The etiology of CVD involves a complex interplay of genetic, environmental, and lifestyle factors. However, traditional diagnosis, prognosis and treatment approaches overlooks this multifaceted nature. Thus, this study aims to delve deeper into the complexities of CVD by leveraging multi-omics data from Chinese multicenter cohorts and international cohorts. We will integrate various omics layers, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, radiomics and clinical data, to unravel the intricate interactions and mechanisms underlying CVD. This comprehensive approach will enhance our understanding of CVD pathogenesis and enable more precise diagnosis, classification, and treatment strategies. Our methodology involves meticulous feature selection and the development of advanced machine learning models to analyze the multi-omics data comprehensively. Through clustering analysis and statistical techniques, we aim to identify distinct subtypes of CVD and their associated biomarkers. This information will facilitate personalized interventions tailored to individual patients, ultimately improving treatment outcomes. The project will span a duration of 36 months. By refining CVD diagnosis and classification, our research has the potential to revolutionize cardiovascular care. Early detection, personalized treatment, and targeted interventions based on individual characteristics will lead to improved patient outcomes and better management of CVD. Additionally, our findings may contribute to broader public health initiatives focused on disease prevention and population health improvement.4 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 15539 | Association between triglyceride glucose-body mass index and the trajectory of cardio-renal-metabolic multimorbidity: insights from multi-state modelling | Haoxian Tang (+18) | 2025 | Cardiovascular Diabetology |
| 15641 | Association of neutrophil to high density lipoprotein cholesterol ratio with aortic dissection and aneurysm risk: epidemiological insights from prospective cohort study based on UK biobank | Cuihong Tian (+4) | 2025 | BMC Public Health |
| 15642 | Data-driven discovery of midlife cardiometabolic profile associated with incident early-onset and late-onset dementia | Jiang Li (+10) | 2025 | Diabetes Obesity and Metabolism |
| 15533 | The global burden and biomarkers of cardiovascular disease attributable to ambient particulate matter pollution | Haoxian Tang (+18) | 2025 | Journal of Translational Medicine |
Enabling scientific discoveries that improve human health