Skip to content

Systems-level proteomic reprogramming reveals mitochondrial restoration and inhibition of Rho GTPase-mediated cytoskeletal and inflammatory signaling in CKD

Sep 2026 · bioRxiv · 0 citations · 41 references
Biology

Abstract

Chronic kidney disease (CKD) is a progressive disorder characterized by metabolic dysfunction, mitochondrial impairment, oxidative stress, and chronic inflammation, ultimately leading to irreversible renal damage. Despite advances in understanding CKD pathophysiology, effective therapies targeting these interconnected molecular processes remain limited. In this study, we performed a comprehensive data-independent acquisition (DIA)-based proteomic analysis to investigate the molecular alterations associated with CKD and to evaluate the therapeutic impact of DVA treatment. Using a CKD model with three treatment conditions (DVA, KY, and DVA+KY) alongside disease and healthy controls, we quantified global proteomic changes and applied statistical filtering (fold change ≥2, p ≤0.05) followed by K-means clustering (k=10). Distinct protein clusters revealed bidirectional modulation upon DVA treatment. Notably, Cluster 1 comprised proteins downregulated in CKD but significantly restored following DVA administration, while Cluster 2 included proteins elevated in CKD that were suppressed by DVA. Pathway enrichment and network analyses demonstrated that Cluster 1 proteins were predominantly associated with mitochondrial function, oxidative phosphorylation, and metabolic processes, whereas Cluster 2 proteins were enriched in immune signaling, oxidative stress, cytoskeletal remodeling, and proteostasis pathways. At the molecular level, DVA treatment restored key mitochondrial and metabolic regulators, including components of the electron transport chain (e.g., COX5A, NDUFS5, SDHB) and redox homeostasis proteins, indicating recovery of cellular bioenergetics. Concurrently, DVA suppressed inflammatory mediators (STAT2, IFI47, GBP2), oxidative stress-related proteins (CYBB, PRDX5), and cytoskeletal regulators linked to renal injury (ARHGEF12, FMNL2). Network and Reactome analyses further confirmed coordinated modulation of interconnected biological systems rather than isolated protein changes. Collectively, our findings demonstrate that DVA exerts a dual therapeutic effect by restoring essential mitochondrial and metabolic pathways while simultaneously suppressing inflammation, oxidative stress, and cytoskeletal dysregulation in CKD. This systems-level proteomic reprogramming highlights DVA as a promising candidate for CKD intervention and provides mechanistic insights into disease progression and therapeutic targeting.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

Google DeepMind Blog Nov 25, 2025

AlphaFold: Five years of impact

Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.