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. 2023 Jul 5;21(1):245.
doi: 10.1186/s12916-023-02962-z.

Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study

Jie-Sheng Lin  1   2 , Jana Nano  1   3 , Agnese Petrera  4 , Stefanie M Hauck  4 , Tanja Zeller  5   6 , Wolfgang Koenig  7   8   9 , Christian L Müller  10   11   12   13 , Annette Peters  1   3   14 , Barbara Thorand  15   16
Affiliations

Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study

Jie-Sheng Lin et al. BMC Med. .

Abstract

Background: Due to the asymptomatic nature of the early stages, chronic kidney disease (CKD) is usually diagnosed at late stages and lacks targeted therapy, highlighting the need for new biomarkers to better understand its pathophysiology and to be used for early diagnosis and therapeutic targets. Given the close relationship between CKD and cardiovascular disease (CVD), we investigated the associations of 233 CVD- and inflammation-related plasma proteins with kidney function decline and aimed to assess whether the observed associations are causal.

Methods: We included 1140 participants, aged 55-74 years at baseline, from the Cooperative Health Research in the Region of Augsburg (KORA) cohort study, with a median follow-up time of 13.4 years and 2 follow-up visits. We measured 233 plasma proteins using a proximity extension assay at baseline. In the discovery analysis, linear regression models were used to estimate the associations of 233 proteins with the annual rate of change in creatinine-based estimated glomerular filtration rate (eGFRcr). We further investigated the association of eGFRcr-associated proteins with the annual rate of change in cystatin C-based eGFR (eGFRcys) and eGFRcr-based incident CKD. Two-sample Mendelian randomization was used to infer causality.

Results: In the fully adjusted model, 66 out of 233 proteins were inversely associated with the annual rate of change in eGFRcr, indicating that higher baseline protein levels were associated with faster eGFRcr decline. Among these 66 proteins, 21 proteins were associated with both the annual rate of change in eGFRcys and incident CKD. Mendelian randomization analyses on these 21 proteins suggest a potential causal association of higher tumor necrosis factor receptor superfamily member 11A (TNFRSF11A) level with eGFR decline.

Conclusions: We reported 21 proteins associated with kidney function decline and incident CKD and provided preliminary evidence suggesting a potential causal association between TNFRSF11A and kidney function decline. Further Mendelian randomization studies are needed to establish a conclusive causal association.

Keywords: Chronic kidney disease; Cohort study; Glomerular filtration rate; Mendelian randomization; Proteomics.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of study participants. Abbreviations: eGFRcr, creatinine-based estimated glomerular filtration rate; KORA S4/F4/FF4, the Cooperative Health Research in the Region of Augsburg (KORA) cohort study at baseline ( S4), first follow-up (F4) and second follow-up (FF4)
Fig. 2
Fig. 2
Association of 233 proteomic biomarkers with the annual rate of change in eGFRcr. Detailed results of beta coefficients and FDR for the association of 233 proteins with change in eGFRcr are presented in Additional file 1: Table S6 for model 2. Abbreviations: eGFRcr, creatinine-based estimated glomerular filtration rate; FDR, Benjamini–Hochberg false-discovery rate. Full names of the biomarkers can be found in Additional file 1: Table S1
Fig. 3
Fig. 3
Overlap of proteomic biomarkers associated with kidney function decline and incident CKD. Kidney function decline includes both the annual rate of change in eGFRcr and the annual rate of change in eGFRcys. Detailed results are presented in Additional file 1: Table S10. Abbreviations: CKD, chronic kidney disease; eGFRcr, creatinine-based estimated glomerular filtration rate; eGFRcys, cystatin C-based estimated glomerular filtration rate; HR, hazard ratio. Full names of the biomarkers can be found in Additional file 1: Table S1
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