Proteome–Metabolome–Phenome Triangulation Identifies Causal Bridges Between AKI and CKD

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Proteome–Metabolome–Phenome Triangulation Identifies Causal Bridges Between AKI and CKD

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Co-author 1

Shen Chen oliver0115@connect.hku.hk The University of Hong Kong Li Ka Shing Faculty of Medicine Hong Kong Hong Kong, China *

Co-author 2

Shucheng Qi qsc@mail.sdu.edu.cn Shandong University Software College Shandong China -

Co-author 3

Zhendong Tian tianzhd2024@lzu.edu.cn Lanzhou University The Second Hospital & Clinical Medical School Lanzhou China -

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Haiyong Chen haiyong@hku.hk The University of Hong Kong School of Chinese Medicine Hong Kong Hong Kong, China -

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Introduction

Acute kidney injury (AKI) is a recognized risk factor for the development of chronic kidney disease (CKD), while CKD itself increases susceptibility to AKI. However, the molecular and metabolic mechanisms underlying this bidirectional relationship remain poorly characterized. To address these challenges, integrative multi-omics analyses combined with Mendelian randomization (MR) could offer robust frameworks for elucidating causal pathways and cross-dimensional interactions between biological layers.

Methods

An integrative analysis using large genome-wide association studies (GWAS) for AKI and CKD across diverse populations, integrated with metabolomics GWAS, multiple protein quantitative trait locus (pQTL) datasets, and phenome-wide data from FinnGen and the UK Biobank (UKB) were conducted. The bidirectional two-step MR alongside multivariable MR were employed to evaluate causal mediation effects. The integrative network MR framework across proteomics, metabolomics, and clinical phenotypes was performed to delineate crosstalk pathways and bio-pathological mediators underlying AKI-CKD interplay.

Results

Within the two-step/multivariable MR framework, we identified a set of protein mediators, e.g., PLG, MANSC4, ANXA2, CD59, directionally concordant mediation. At the metabolite level, we found that pyroglutamate was a suggestive mediation, implicating the glutathione cycle, redox homeostasis, and amino-acid metabolism. Stratified analyses indicated stronger effects at advanced CKD stages, aligning with progressive kidney functional decline. Phenome-wide association scans in FinnGen and UKB revealed risk patterns for kidney-related diseases and measurable clinical indices that were concordant with MR. Robustness analyses including tests against reverse causation, colocalization, and pleiotropy sensitivity together with multi-cohort checks, supported the stability of these findings. Collectively, we delineate a mediation map spanning proteins, metabolites, and clinical phenotypes.

Conclusion

Our integrative analyses demonstrate bidirectional causal links between AKI and CKD, suggesting certain proteins, metabolites, and clinical traits as key mediators, and delineate core pathways underlying their comorbidity.

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