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Reshaping the chromatin landscape in HUVECs from small-for-gestational-age newborns
Lingling Yan, … , Liang Gong, Yanfen Zhu
Lingling Yan, … , Liang Gong, Yanfen Zhu
Published April 22, 2025
Citation Information: JCI Insight. 2025;10(8):e186812. https://doi.org/10.1172/jci.insight.186812.
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Research Article Angiogenesis Cardiology

Reshaping the chromatin landscape in HUVECs from small-for-gestational-age newborns

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Abstract

Small for gestational age (SGA), with increased risk of adult-onset cardiovascular diseases and metabolic syndromes, is known to associate with endothelial dysfunction, but the pathogenic mechanisms remain unclear. In this study, the pathological state of human umbilical vein endothelial cells (HUVECs) from SGA individuals was characterized by presenting increased angiogenesis, migration, proliferation, and wound healing ability relative to their normal counterparts. Genome-wide mapping of transcriptomes and open chromatins unveiled global gene expression alterations and chromatin remodeling in SGA-HUVECs. Specifically, we revealed increased chromatin accessibility at active enhancers, along with dysregulation of genes associated with angiogenesis, and further identified CD44 as the key gene driving HUVECs’ dysfunction by regulating pro-angiogenic genes’ expression and activating phosphorylated ERK1/2 and phosphorylated endothelial NOS expression in SGA. In SGA-HUVECs, CD44 was abnormally upregulated by 3 active enhancers that displayed increased chromatin accessibility and interacted with CD44 promoter. Subsequent motif analysis uncovered activating protein-1 (AP-1) as a crucial transcription factor regulating CD44 expression by binding to CD44 promoter and associated enhancers. Enhancers CRISPR interference and AP-1 inhibition restored CD44 expression and alleviated the hyperangiogenesis of SGA-HUVECs. Together, our study provides a foundational understanding of the epigenetic alterations driving pathological angiogenesis and offers potential therapeutic insights into addressing endothelial dysfunction in SGA.

Authors

Lingling Yan, Zhimin Zhou, Shengcai Chen, Xin Feng, Junwen Mao, Fang Luo, Jianfang Zhu, Xiuying Chen, Yingying Hu, Yuan Wang, Bingbing Wu, Lizhong Du, Chunlin Wang, Liang Gong, Yanfen Zhu

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Figure 1

Distinctive phenotypes of HUVECs derived from SGA and AGA individuals.

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Distinctive phenotypes of HUVECs derived from SGA and AGA individuals.
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(A) Schematic overview of the study design. CRISPRi, CRISPR interference; Hi-C, high-throughput chromosome conformation capture; OE, overexpression; TF, transcription factor. (B) Representative images of the cross section of umbilical cord tissues stained by H&E. The enlarged parts represent umbilical veins. Scale bars: 1 mm (left) and 200 μm (right); n = 4 per group. (C) Representative immunofluorescence staining of primary HUVECs’ identity; scale bar: 20 μm; n = 4 per group. (D) Representative images of angiogenesis; scale bar: 100 μm. (E) Analysis of the total tube length, total tube branching length, and total segment length for samples shown in Supplemental Figure 1A (n = 9 AGA and 12 SGA). (F) Representative images of scratches at 0 hours and 12 hours; scale bar: 200 μm. (G) Analysis of the percentage of migration area; n = 4 per group. (H) Representative images of HUVECs that migrated through the pores; scale bar: 100 μm. (I) Analysis of percentage of migrating cell number; n = 4 per group. (J) Analysis of EdU assay; n = 4 per group. (K) Analysis of CCK8 assay results at 0 hours, 24 hours, 48 hours, and 72 hours; n = 4 per group. Two-way ANOVA with Holm-Šídák multiple comparisons test was used for comparing cell proliferation at different times. (L) Analysis of glucose consumption; n = 4 per group. Data presented as mean ± SEM. Statistical analysis was performed using 2-tailed unpaired Student’s t test.

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