WP 4
General Population of Bavaria

Prof. Dr. Annette Peters

Director of the Institute of Epidemiology, Helmholtz Munich, Germany

Work Package 4: The General Population of Bavaria

The goal of AP4 is to develop innovative strategies for personalized prevention of heart attacks and strokes in the general population. The project is based on data from the KORA study, one of the largest population-based cohorts in Germany, with over 17,000 participants and extensive long-term follow-up.

Key Topics:

  • Omics Analyses & Data Integration:
    Genomic, metabolic, and proteomic characterization of the KORA population. Development of an integrated omics database for comprehensive analyses.
  • Digital Infrastructure:
    Development of a secure platform for analyzing individual data and testing new predictive algorithms.
  • Predictive Models & Prevention:
    Derivation of innovative algorithms for risk prediction and simulation of personalized prevention approaches.
  • Transparency & Interaction:
    Making results available to the public via user-friendly online applications.

Added Value:
WP4 creates a unique research database and digital tools to identify risk factors early and optimize prevention strategies for the Bavarian population.

Results Work Package 4

The KORA Cohort and Cardiovascular Research in the General Population of Bavaria

Overview

Work Package 4 focuses on the KORA cohort, one of the most comprehensive long-term studies on the prediction of cardiovascular disease in Bavaria. The goal is to improve risk prediction, prevention, and care through the integration of innovative OMICS data and digital infrastructure.

Key Findings

  • The KORA Cohort as a Foundation:
    • The KORA Cohort as a Foundation: The KORA cohort comprises 17,602 participants from the Augsburg region and has been providing valuable long-term data on heart attacks, strokes, and diabetes since 1984.
    • As part of DigiMed Bayern, large portions of the cohort were characterized using genomics, transcriptomics, proteomics, and metabolomics.
  • Innovative OMICS analyses:
    • New OMICS data (proteomics, genomics, transcriptomics, metabolomics) were obtained from stored blood samples.
    • In total, for example, 9,201 proteomics, 4,032 genomics, 1,930 transcriptomics, and 3,922 metabolomics datasets were generated.
  • Gender-specific and lifetime analyses:
    • The KORA cohort is particularly well-suited for gender-specific analyses (50% men and 50% women).
    • Lifetime analyses show changes in risk factors and diseases over several decades.
  • Prediction algorithms:
    • The Framingham Risk Score for 30-year risk was calculated using KORA data and implemented in the HerzFit App (WP1.2).
    • Genetic models for predicting the risk of coronary heart disease and stroke were developed and compared.
  • Data protection and infrastructure:
    • Establishment of the DigiMed Secure Cloud at the LRZ for the secure storage and processing of research data.
    • Improvement of metadata and development of data management plans according to FAIR principles.
  • Public outreach:
    • Results were made available to the public and study participants through brochures, websites, and scientific publications.

Sustainability and Outlook

  • Completion of pending scientific publications and further analyses on multi-omics and improved risk prediction.
  • Expansion of the use of the DigiMed Secure Cloud and integration of KORA data into future research projects.
  • Implementation of the findings in a digitally supported intervention study within the EU project STAGE – Stay Healthy Through Ageing.
Conclusion for Work Package 4

Work Package 4 has laid a groundbreaking foundation for personalized medicine and health research in Bavaria through the KORA cohort and innovative OMICS analyses. The results enable more accurate risk prediction, gender-specific care, and the sustainable use of research data for future projects.