Kidney biomarkers and cardiovascular risk in South Tyrol population-based studies
We recently published a paper on PLOS ONE journal investigating how we can integrate routinely measured kidney biomarkers to predict cardiovascular risk over 10 years.
Chronic kidney disease (CKD) is one of the most overlooked diseases, with an estimated 8.4 million patients worldwide. Additionally, it is estimated to be the fifth leading cause of death by 2040, suggesting an emerging health issue in countries with aging societies.
CKD is clinically defined by an index called estimated glomerular filtration rate (eGFR), which is calculated based on serum creatinine (an item in routine blood exam), sex, and age. However, serum creatinine is known to be affected by muscle mass and other biological functions. Therefore, eGFR, a combination of serum cystatin and serum creatinine, has been shown to improve performance. However, incorporation of other kidney-related biomarkers has not been investigated.
In the present study, we aimed to integrate four biomarkers related to kidney function that are routinely measured using a statistical method called structural equation modeling and compared them with cardiovascular risk.
More than 1300 participants in both of the two previous population-based studies in South Tyrol (Microisolates in South Tyrol study (MICROS) and Cooperative Health Research in South Tyrol study (CHRIS)) included in this study. The target population was divided into two parts: Model-building set & Longitudinal dataset (Figure. Top left). Our study used creatinine-based eGFR (eGFRcre), cystatin C-based eGFR (eGFRcys), blood urea nitrogen (BUN), and uric acid (UA), and integrated in the Model-building set. In the Longitudinal set, we compared the discriminative ability of presence of 10-year cardiovascular risk with existing kidney function indices (Figure. Top right). The results showed that our model outperformed than existing formulas (eGFRcre and eGFRcrecys), while the performance of eGFRcys alone was comparable (Figure. Bottom).
In conclusion, our model showed higher performance than eGFRcre, which is commonly used in clinical practice, suggesting that it is a promising model. On the other hand, it could not outperform eGFRcys. The implication of our results is that eGFRcys may be an important and convenient indicator for CVD risk determination.
Read the full article here: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0280600
The MICROS study was funded by the department of Innovation, Research and University of the Autonomous Province of Bolzano-South Tyrol and South Tyrolean Sparkasse Foundation.
The CHRIS study is a collaborative effort between the Eurac Research Institute for Biomedicine and the Healthcare System of the Autonomous Province of Bozen/Bolzano (Südtiroler Sanitätsbetrieb/Azienda Sanitaria dell’Alto Adige). We thank all study participants from the middle and upper Vinschgau/Val Venosta, the general practitioners, and the personnel of the Hospital of Schlanders/Silandro for their support and collaboration. Furthermore, we thank the study assistants and the biobank of the Institute for Biomedicine for data and sample collection and elaboration.
The CHRIS biobank was assigned the “Bioresource Research Impact Factor” (BRIF) code BRIF6107. The CHRIS study is funded by the Department of Innovation, Research and the University of the Autonomous Province of Bozen/Bolzano, Italy.
RF has been supported by the Autonomous Province of Bozen/Bolzano – Department for Innovation, Research and University in the frame of the Seal of Excellence Programme (nr.CUP/D55F20002560003) and the Uehara Memorial Foundation, Oversea Fellowship for Post-doc Students. The authors thank the Department of Innovation, Research and University of the Autonomous Province of Bozen/Bolzano for covering the Open Access publication costs.
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