Biology subjects

Choi, H. Y.

Publications and source records attributed to Choi, H. Y..

5 recordsLinked to original sources

bioRxiv2026

Macrophage-Derived 25-Hydroxycholesterol Drives Statin-Associated Acute Kidney Injury

Although acute kidney injury (AKI) has been implicated as a potential adverse effect of statin therapy, experimental evidence supporting this association remains limited. Here, we investigated whether elevated levels of 25-hydroxycholesterol (25-HC), an oxysterol produced by activated macrophages and monocytes, increase susceptibility to statin-induced AKI. We found that atorvastatin and fluvastatin induced cell death in proximal tubular cells when combined with 25-HC. Consistently, administration of low-dose lipopolysaccharide triggered AKI in statin-treated mice. Mechanistically, impaired protein prenylation disrupted the autophagosome-lysosome pathway in proximal tubular cells. AKI was attenuated by mevalonate supplementation, which restored protein prenylation, and by macrophage/monocyte depletion, which reduced the cellular sources of 25-HC. Furthermore, combined exposure to fluvastatin and 25-HC increased kidney injury molecule-1 (KIM-1) expression in human induced pluripotent stem cell-derived kidney organoids. Together, these findings suggest that elevated macrophage-derived 25-HC under conditions of infection, inflammation, or major surgery may increase susceptibility to statin-induced AKI. Our study identifies a previously unrecognized interaction between statins and 25-HC and suggests potential strategies to mitigate kidney injury while preserving the therapeutic benefits of statins.

pharmacology and toxicology↗

bioRxiv2025

Lung Adenocarcinoma Just Desserts: An Expanding Pie of Activating Oncogenes or a Layer Cake of Integrated Alterations

The molecular landscape of lung adenocarcinoma (LUAD) is often summarized as a "pie chart" of driver oncogenes, suggesting identification and targeting of oncogenic drivers is the best clinical approach. However, this model oversimplifies LUAD biology. Patients with identical RAS or RAF mutations exhibit heterogeneous signaling influenced by co-mutations, transcriptional programs, and lineage context. We propose a hierarchical framework integrating oncogenes within cellular context by examining canonical EGFR mutations. We defined an EGFR mutation signature (mSig) by identifying differentially expressed genes in EGFR-mutant LUADs. Semi-supervised clustering and machine learning models were used to test performance and reproducibility across independent datasets. We analyzed molecular subtypes, lineage markers, co-occurring mutations, and candidate drug targets in EGFR-mSig positive (+) versus negative (-) tumors. The EGFR mSig showed robust classification performance across datasets (AUROC = 0.83-0.95; mean NPV = 96.3%). Validated unsupervised gene expression subtypes and lung lineage markers were closely aligned with EGFR mSig status. mSig(+) tumors were identified, even in tumors without EGFR mutations. A subset of canonical RAS mutations mirrored the EGFR mutation pattern. EGFR-mutant/mSig(-) tumors were enriched for non-Bronchioid subtypes and had co-mutations in TP53 or RAS. Coordinated mutations were identified including RAS, KEAP1, STK11, TP53, and CDKN2A, supportive of prior reports. In sum, novel EGFR mSig that captures the transcriptional footprint of EGFR activation, revealed a subset of EGFR wildtype LUADs with "mutant-like" features. Lineage-informed classification highlights subtype-dependent oncogene activity and supports new therapeutic strategies. A context-specific association between RAS mutation and expression of the dual-specificity phosphatase gene DUSP4 may have therapeutic potential.

genomics↗

bioRxiv2024

Associations Between Prenatal Vitamin D and Placental Gene Expression

BackgroundVitamin D is a hormone regulating gene transcription. Prenatal vitamin D has been linked to immune and vascular function in the placenta, a key organ of pregnancy. To date, studies of vitamin D and placental gene expression have focused on a limited number of candidate genes. Transcriptome-wide RNA sequencing can provide a more complete representation of the placental effects of vitamin D. ObjectiveWe investigated the association between prenatal vitamin D levels and placental gene expression in a large, prospective pregnancy cohort. MethodsParticipants were recruited in Shelby County, Tennessee in the Conditions Affecting Neurocognitive Development and Learning in Early childhood (CANDLE) study. Vitamin D level (plasma total 25-hydroxyvitatmin D, [25(OH)D]) was measured at mid-pregnancy (16-28 weeks gestation) and delivery. Placenta samples were collected at birth. RNA was isolated and sequenced. We identified differentially expressed genes (DEGs) using adjusted linear regression models. We also conducted weighted gene co-expression network analysis (WGCNA). ResultsThe median 25(OH)D of participants was 21.8 ng/mL at mid-pregnancy (N=774, IQR: 15.4-26.5 ng/mL) and 23.6 ng/mL at delivery (N=753, IQR: 16.8-29.1 ng/mL). Placental expression of 25 DEGs was associated with 25(OH)D at mid-pregnancy, but no DEG was associated with 25(OH)D at delivery. DEGs were related to energy metabolism, cytoskeletal function, and RNA transcription. Using WGCNA, we identified 2 gene modules whose expression was associated with 25(OH)D at mid-pregnancy and 1 module associated with 25(OH)D at delivery. These modules were enriched for genes related to mitochondrial and cytoskeletal function, and were regulated by transcription factors including ARNT2, BHLHE40, FOSL2, JUND, and NFKB1. ConclusionsOur results indicate that 25(OH)D during mid-pregnancy, but not at delivery, is associated with placental gene expression at birth. Future research is needed to investigate a potential role of vitamin D in programming placental mitochondrial metabolism, intracellular transport, and transcriptional regulation during pregnancy.

developmental biology↗

bioRxiv2023

Matrix Linear Models for connecting metabolite composition to individual characteristics

AO_SCPLOWBSTRACTC_SCPLOWHigh-throughput metabolomics data provide a detailed molecular window into biological processes. We consider the problem of assessing how the association of metabolite levels with individual (sample) characteristics such as sex or treatment may depend on metabolite characteristics such as pathway. Typically this is one in a two-step process: In the first step we assess the association of each metabolite with individual characteristics. In the second step an enrichment analysis is performed by metabolite characteristics among significant associations. We combine the two steps using a bilinear model based on the matrix linear model (MLM) framework we have previously developed for high-throughput genetic screens. Our framework can estimate relationships in metabolites sharing known characteristics, whether categorical (such as type of lipid or pathway) or numerical (such as number of double bonds in triglycerides). We demonstrate how MLM offers flexibility and interpretability by applying our method to three metabolomic studies. We show that our approach can separate the contribution of the overlapping triglycerides characteristics, such as the number of double bonds and the number of carbon atoms. The proposed method have been implemented in the open-source Julia package, MatrixLM. Data analysis scripts with example data analyses are also available.

bioinformatics↗

bioRxiv2020

Inhibition of lysyl oxidase-like 2 ameliorates folic acid-induced renal tubulointerstitial fibrosis

Tubulointerstitial fibrosis is characterized by accumulation of the extracellular matrix in the interstitium. Lysyl oxidase-like 2 (LOXL2), a member of the lysyl oxidase family, is known for promoting cancer metastasis, invasion, and stromal fibrosis in various organs. Our previous study demonstrated expression of LOXL2 in kidney podocytes and tubular epithelial cells, and the association between elevated LOXL2 and tubulointerstitial fibrosis. The present study evaluated the effect of LOXL2 inhibition using an inhibitory monoclonal antibody (AB0023) on tubulointerstitial fibrosis in a folic acid-induced tubulointerstitial fibrosis mouse model. We also evaluated the association of LOXL2 with epithelial-mesenchymal transformation related molecules in vitro using HK-2 cells. Our data demonstrate that AB0023 prevented the progression of tubulointerstitial fibrosis significantly, as determined by trichrome and picro-sirius red staining, as well as the total collagen assay. The mean expression of phosphorylated Smad2 and Smad4 was lower in the AB0023-treated group although it was not statistically significant. Following transforming growth factor-{beta} (TGF-{beta}) challenge, LOXL2-deficient HK-2 cells exhibited significantly lower expression of the mesenchymal markers vimentin and fibronectin than control HK-2 cells. In conclusion, LOXL2 inhibition ameliorates renal fibrosis through the TGF-{beta}/Smad signalling pathway.

pathology↗