PLASMA AND URINARY PROTEOMIC PROFILES ASSOCIATED WITH RISK OF DISEASE PROGRESSION IN AUTOSOMAL DOMINANT POLYCYSTIC KIDNEY DISEASE

The mechanisms underlying disease progression in autosomal dominant polycystic kidney disease (ADPKD) remain incompletely understood, and current treatments and risk stratification tools offer limited efficacy. Proteomic profiling offers a powerful approach to uncover molecular pathways and biomarkers linked to disease progression. To address these existing knowledge gaps, we applied an untargeted proteomics strategy to characterize plasma and urine protein profiles associated with clinical disease progression in ADPKD.

We included patients with ADPKD from the national ongoing DIPAK observational study, excluding patients that used tolvaptan or somatostatin analogues at baseline. Protein quantification was performed using the Olink Explore 1536 platform, covering 1472 proteins in baseline plasma and spot urine samples. Differential plasma and urinary protein expression was investigated based on rate of eGFR decline (< or ≥ 3 ml/min/1.73m2/year) and Mayo Imaging Class (MIC 1C-E vs. 1A/B). Associations between protein expression and disease progression, defined by annual eGFR decline and height-adjusted total kidney volume (HtTKV) growth, and a composite endpoint of kidney failure or ≥30% eGFR decline, were evaluated using linear regression and Cox proportional hazards survival analysis. All models were adjusted for baseline eGFR, sex, and urinary creatinine (for urinary data) to minimize confounding. Pathway enrichment analysis was used to identify biological pathways most strongly associated with disease progression. In addition to baseline eGFR, sex, and urinary creatinine (urinary data), we additionally adjusted for age, MIC and pathogenic variant type (established clinical risk factors of disease progression) to determine which proteins are potentially most useful for enhancing clinical risk prediction. Corrections for multiple testing (FDR < 0.05) were applied to all models as appropriate.

We included 651 patients (39.0% male) with a mean ± SD baseline age of 47.3 ± 12.0 years and eGFR of 64.1 ± 28.7 ml/min/1.73m2. The mean eGFR slope was -2.8 ± 1.3 ml/min/1.73m2/year, with a median [Q1, Q3] HtTKV slope of 40.0 [15.8, 84.9] ml/m/year (corresponding to 5.1 [2.8, 7.2] %/year), and 308 patients (47.3%) reached the composite kidney endpoint. Differential expression, linear regression and survival analyses confirmed several known biomarker associations with clinical disease progression in ADPKD (e.g. MMP-7, MCP-1, KIM-1), and revealed numerous novel associations with disease progression (e.g. WFDC2, LIF, IGFBP4). In total, 44 proteins were associated with both functional and volumetric disease progression in plasma and/or urine. Pathway enrichment highlighted several biological pathways associated with accelerated functional and/or volumetric disease progression, including extracellular matrix remodeling, tumour necrosis factor signaling, chemokine receptor binding, and activation of matrix metalloproteinases. Several proteins remained independently associated with kidney outcomes after additional adjustment for MIC and pathogenic variant type, including many not previously reported, highlighting their potential to improve risk prediction in ADPKD.

Our results define distinct plasma and urinary proteomic signatures that reflect several pathways associated with disease progression in ADPKD, and highlight candidate biomarkers for improved risk prediction and therapeutic targeting.