Issue 29, 2022, Issue in Progress

A novel fluorescent digitonin derivative for non-invasive skin cholesterol detection: potential application in atherosclerosis screening

Abstract

There is a great demand for the rapid and non-invasive atherosclerosis screening method. Cholesterol content in the epidermis of the skin is an early biomarker for atherosclerosis. Risk assessment of atherosclerosis can be achieved by measuring cholesterol in the epidermis. Here, we synthesised a new fluorescent digitonin derivative (FDD) for the non-invasive detection of skin cholesterol. The results of fluorescence spectroscopy studies indicated that the probe exhibited desirable selectivity for cholesterol. The proof-of-concept preclinical study confirmed that FDD can detect different concentrations of skin cholesterol; patients diagnosed with atherosclerotic cardiovascular disease and the at-risk atherosclerosis group exhibited higher skin cholesterol content than the normal group. The area under the ROC curve for distinguishing the normal/disease group was 0.9228 (95% confidence interval, 0.8938 to 0.9518), and the area under the ROC curve for distinguishing the normal/risk group was 0.9422 (95% confidence interval, 0.9178 to 0.9665). We anticipate that this non-invasive skin cholesterol test may be used as a risk assessment tool for atherosclerosis screening in a large population for further examination and intervention in high-risk populations.

Graphical abstract: A novel fluorescent digitonin derivative for non-invasive skin cholesterol detection: potential application in atherosclerosis screening

Supplementary files

Article information

Article type
Paper
Submitted
28 Mar 2022
Accepted
27 May 2022
First published
22 Jun 2022
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2022,12, 18397-18406

A novel fluorescent digitonin derivative for non-invasive skin cholesterol detection: potential application in atherosclerosis screening

J. Ni, Y. Liu, H. Hong, X. Kong, Y. Han, L. Zhang, Y. Zhang, Y. Zhang, C. Hua, Q. Wang, X. Wang, Y. Huang, W. YiKun and D. Meili, RSC Adv., 2022, 12, 18397 DOI: 10.1039/D2RA01982E

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