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Potential Therapeutic Targeting of lncRNAs in Cholesterol Homeostasis

Ye, Wen-Chu, Huang, Shi-Feng, Hou, Lian-Jie, Long, Hai-Jiao, Yin, Kai, Hu, Ching Yuan, Zhao, Guo-Jun·2021·Frontiers in Cardiovascular Medicine

Abstract

Maintaining cholesterol homeostasis is essential for normal cellular and systemic functions. Long non-coding RNAs (lncRNAs) represent a mechanism to fine-tune numerous biological processes by controlling gene expression. LncRNAs have emerged as important regulators in cholesterol homeostasis. Dysregulation of lncRNAs expression is associated with lipid-related diseases, suggesting that manipulating the lncRNAs expression could be a promising therapeutic approach to ameliorate liver disease progression and cardiovascular disease (CVD). However, given the high-abundant lncRNAs and the poor genetic conservation between species, much work is required to elucidate the specific role of lncRNAs in regulating cholesterol homeostasis. In this review, we highlighted the latest advances in the pivotal role and mechanism of lncRNAs in regulating cholesterol homeostasis. These findings provide novel insights into the underlying mechanisms of lncRNAs in lipid-related diseases and may offer potential therapeutic targets for treating lipid-related diseases.

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  • Several DEGs previously associated with lipid metabolism were identified, including MIAT, COMT, NRP1, VEGFB, GRAMD1B, DSEL, and FUT9 associated with glycan structure.

    “We identified several DEGs that have been previously associated with lipid metabolism, including MIAT, COMT, NRP1, VEGFB, GRAMD1B, DSEL56–62, as well as FUT9 associated with glycan structure63,64 (Fig. 4a).”

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Metadata

Authors
Ye, W.-C., Huang, S.-F., Hou, L.-J., Long, H.-J., Yin, K., Hu, C. Y., & Zhao, G.-J.
Venue
Frontiers in Cardiovascular Medicine
Published
2021-06-10
Volume
8
ISSN
2297-055X
Cited by
19
References
3

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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