ASN's Mission

To create a world without kidney diseases, the ASN Alliance for Kidney Health elevates care by educating and informing, driving breakthroughs and innovation, and advocating for policies that create transformative changes in kidney medicine throughout the world.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on X

Kidney Week

Please note that you are viewing an archived section from 2021 and some content may be unavailable. To unlock all content for 2021, please visit the archives.

Abstract: PO2289

Estimated Glomerular Filtration Rate (eGFR) and Myocardial Fibrosis Biomarkers in Hypertensives with and Without CKD

Session Information

Category: CKD (Non-Dialysis)

  • 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

  • Watanabe, Shota, University Hospitals, Cleveland, Ohio, United States
  • Chen, Zhengyi, Case Western Reserve University, Cleveland, Ohio, United States
  • Tatsuoka, Curtis, Case Western Reserve University, Cleveland, Ohio, United States
  • Rahman, Mahboob, University Hospitals, Cleveland, Ohio, United States
  • Wright, Jackson T., University Hospitals, Cleveland, Ohio, United States
  • Dobre, Mirela A., University Hospitals, Cleveland, Ohio, United States
Background

CKD leads to accumulation of fibrotic tissue in the myocardium with subsequent loss of cardiac function. Two circulating biomarkers of collagen type I and III (PICP and P3NP) correlate with the amount of cardiac collagen deposition. Galectin 3 (Gal-3), a predictor of heart failure, is used to stratify patients at increased cardiovascular risk. We aimed to assess the association between eGFR and Gal-3, PICP, and PIIINP levels in individuals with and without CKD enrolled in the Systolic Blood Pressure Intervention Trial (SPRINT).

Methods

A random sample of 1026 SPRINT participants 50 years or older were included in the study. Baseline demographic, anthropometric, co-morbid conditions and laboratory data were examined univariately for association with quartiles of Gal-3, CICP and PIIINP. The statistically significant variables were chosen for the multivariate quantile regressions at median (MQR) to assess the association between baseline eGFR and each biomarker.

Results

The mean age (SD) was 68.3±9.9 years, and 38.4% had CKD. In MQR models, baseline eGFR was negatively associated with Gal-3, PICP and PIIINP levels.(Figure) Similar results were found in participants with CKD, but not in participants without CKD, with significant correlation between eGFR with Gal 3 and PIIINP, but not with PICP. In combination, PIIINP was correlated with PICP (Coef 0.26, 95%CI (0.17, 0.35), p<0.001)), and Gal3 (Coef (0.35, 95%CI (0.26, 0.43), p<0.001) in the CKD subgroup, but not in the non-CKD subgroup (p=0.10, and p=0.07 respectively).

Conclusion

CKD status modifies the association between myocardial fibrosis biomarkers and eGFR, with high serum Gal-3, CICP, and PIIINP levels associated with low eGFR. Future research is needed to elucidate whether there is a causal link between kidney function decline and risk for myocardial fibrosis.

Quantile Regressions for eGFR and Myocardial Fibrosis Biomarkers

Funding

  • Other NIH Support