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The German Centre for Cardiovascular Research (DZHK) is one of the German Centres for Health Research and aims to conduct early and guideline-relevant studies to develop new therapies and diagnostics that impact the lives of people with cardiovascular disease. Therefore, DZHK members designed a collaboratively organised and integrated research platform connecting all sites and partners. The overarching objectives of the research platform are the standardisation of prospective data and biological sample collections among all studies and the development of a sustainable centrally standardised storage in compliance with general legal regulations and the FAIR principles. The main elements of the DZHK infrastructure are web-based and central units for data management, LIMS, IDMS, and transfer office, embedded in a framework consisting of the DZHK Use and Access Policy, and the Ethics and Data Protection Concept. This framework is characterised by a modular design allowing a high standardisation across all studies. For studies that require even tighter criteria additional quality levels are defined. In addition, the Public Open Data strategy is an important focus of DZHK. The DZHK operates as one legal entity holding all rights of data and biological sample usage, according to the DZHK Use and Access Policy. All DZHK studies collect a basic set of data and biosamples, accompanied by specific clinical and imaging data and biobanking. The DZHK infrastructure was constructed by scientists with the focus on the needs of scientists conducting clinical studies. Through this, the DZHK enables the interdisciplinary and multiple use of data and biological samples by scientists inside and outside the DZHK. So far, 27 DZHK studies recruited well over 11,200 participants suffering from major cardiovascular disorders such as myocardial infarction or heart failure. Currently, data and samples of five DZHK studies of the DZHK Heart Bank can be applied for.
Background and aims
Prevention measures for cardiovascular diseases (CVD) have shifted their focus from lipoproteins to the immune system. However, low-grade inflammation and dyslipidemia are tightly entangled. The objective of this study was to assess the relations between a broad panel of inflammatory biomarkers and lipoprotein subclass parameters.
Methods
We utilized data from the population-based Study of Health in Pomerania (SHIP-TREND, n = 403). Plasma concentrations of 37 inflammatory markers were measured by a bead-based assay. Furthermore, we employed nuclear magnetic resonance spectroscopy to measure total cholesterol, total triglycerides, total phospholipids as well as the fractional concentrations of cholesterol, triglycerides, phospholipids, ApoA1, ApoA2 and ApoB in all major lipoprotein subclasses. Associations between inflammatory biomarkers and lipoprotein subclasses were analyzed by adjusted linear regression models.
Results
APRIL, BAFF, TWEAK, sCD30, Pentraxin-3, sTNFR1, sTNFR2, Osteocalcin, Chitinase 3-like 1, IFN-alpha2, IFN-gamma, IL-11, IL-12p40, IL-29, IL-32, IL-35, TSLP, MMP1 and MMP2 were related with lipoprotein subclass components, forming two distinct clusters. APRIL had inverse relations to HDL-C (total and subclasses) and HDL Apo-A1 and Apo-A2 content. MMP-2 was inversely related to VLDL-C (total and subclasses), IDL-C as well as LDL5/6-C and VLDL-TG, IDL-TG, total triglycerides as well as LDL5/5-TG and HDL4-TG. Additionally, we identified a cluster of cytokines linked to the Th1-immune response, which were associated with an atherogenic lipoprotein profile.
Conclusion
Our findings expand the existing knowledge of inflammation-lipoprotein interactions, many of which are suggested to be involved in the pathogeneses of chronic non-communicable diseases. The results of our study support the use of immunomodulatory substances for the treatment and possibly prevention of CVD.