ArticleMolecular medicine (Cambridge, Mass.)2026
Integrative machine learning and CRISPR/Cas9 analysis reveals the role of APOE in lipid metabolism-associated kidney fibrosis.
Article in Molecular medicine (Cambridge, Mass.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kidney fibrosis, characterized by excessive extracellular matrix deposition and progressive renal tissue remodeling, frequently culminates in End-stage kidney disease (ESKD). Emerging evidence links dysregulated lipid metabolism to renal fibrogenesis; however, the precise molecular mechanisms connecting these processes remain elusive. Apolipoprotein E (APOE), a central coordinator of lipid transport and metabolic homeostasis, is implicated in various metabolic and inflammatory diseases, yet its specific contribution to renal fibrotic signaling is poorly defined. In this study, we utilized an integrative framework comprising machine learning-assisted transcriptomic analysis, clinical validation, and CRISPR/Cas9 gene editing to elucidate the role of APOE in kidney fibrosis. Machine learning analysis of public transcriptomic datasets pinpointed APOE as a top-ranked gene highly correlated with renal fibrotic signatures and metabolic pathways. Consistently, APOE expression was significantly altered in clinical blood samples from Maintenance hemodialysis patients compared to healthy controls. To mechanistically validate these findings, we generated an in vitro APOE-knockout model using CRISPR/Cas9, followed by Angiotensin II stimulation to induce renal fibrogenesis. APOE ablation profoundly impacted the expression of canonical pro-fibrotic markers (COL1A1, FN1, and α-SMA) alongside crucial lipid metabolism genes (FASN and ACC), as confirmed by quantitative real-time PCR and Western blot analyses. Pathway enrichment further corroborated APOE's role as a critical regulatory node bridging lipid homeostasis and fibrotic cascades in the kidney. Overall, our findings establish APOE as a pivotal regulator of renal fibrotic remodeling, highlighting a direct mechanistic interplay between lipid metabolism and kidney fibrosis. Consequently, therapeutic modulation of APOE-dependent pathways may offer a promising strategy for treating chronic kidney disease and associated fibrotic pathologies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.