| Title: | Integrative analysis identifies novel proteins associated with chronic kidney disease in participants with abnormal glucose metabolism |
| Journal: | Diabetes Research and Clinical Practice |
| Published: | 9 Sep 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40934961/ |
| DOI: | https://doi.org/10.1016/j.diabres.2025.112474 |
Publication 19532
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Abstract
AIM: Chronic kidney disease (CKD) is highly prevalent among individuals with abnormal glucose metabolism. However, limited research has specifically investigated CKD-associated proteins within this high-risk population. To address this gap, our study aimed to identify proteins associated with CKD in participants with abnormal glucose metabolism, potentially informing early detection and targeted therapeutic strategies.</p>
METHODS: We first employed orthogonal partial least squares discriminant analysis (OPLS-DA) to select important proteins and further used Cox proportional hazards models using proteomic data from the UK Biobank to identify candidate proteins associated with CKD in participants with abnormal glucose metabolism. Subsequently, we performed one-sample Mendelian randomization (MR) using individual-level genomic data from the UK Biobank and pQTL summary statistics from the UKB-PPP, applying a two-stage least squares approach. For two-sample MR, we utilized pQTL data from deCODE and CKD GWAS summary statistics derived from the UK Biobank, applying either the Wald ratio or inverse variance weighted (IVW) method. Proteins supported by both observational analyses and at least one MR approach were further evaluated using publicly available databases to determine their novelty. Finally, for proteins consistently identified across all approaches, we assessed tissue specificity, gene expression, and conducted sensitivity analyses to strengthen the robustness of our findings.</p>
RESULTS: Through integrated observational and MR analyses, we identified a total of 45 proteins significantly associated with CKD in participants with abnormal glucose metabolism, among which 11 represent novel discoveries: CD300C, CD300LG, CDNF, CDSN, CHRDL1, ENPP6, LEFTY2, MOG, RSPO3, TNFRSF13B, and MYLPF. Notably, ENPP6 emerged with consistent evidence across all analytic approaches. Observational analyses demonstrated a hazard ratio (HR) of 0.75 (95% CI: 0.63-0.89), while one-sample MR revealed an odds ratio (OR) of 0.32 (95% CI: 0.14-0.73), and two-sample MR produced an OR of 0.60 (95% CI: 0.37-0.98), supporting a protective role of ENPP6 in CKD development. Furthermore, ENPP6 displayed kidney-specific expression, particularly within peritubular and proximal tubular cells. These findings were robustly validated through comprehensive sensitivity analyses.</p>
CONCLUSION: In conclusion, we identified 11 novel proteins associated with CKD in individuals with abnormal glucose metabolism, with ENPP6 emerging as a particularly compelling candidate due to its consistent protective association across multiple analytical approaches. These findings offer promising insights into CKD pathophysiology and highlight ENPP6 as a potential biomarker or therapeutic target. Further research is warranted to elucidate the mechanistic roles of these novel proteins in CKD development and progression.</p>
13 Authors
- Ning Li
- Jingyang Liu
- Guangheng Wu
- Jie Zhang
- Long Liu
- Manqi Zheng
- Haibin Li
- Changwei Li
- Yalu Wen
- Jianguang Ji
- Yang Yu
- Kun Zhao
- Deqiang Zheng
1 Application
| Application ID | Title |
|---|---|
| 95259 | The role of dynamic environmental factors, genetic information, and gene-environment interactions in non-communicable chronic diseases and the development and validation of prediction models for risks |
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