- 건국대학교

	KU Research Team Establishes AI-based Vascular Aging Gene Mapping
	관리자		302		2020.12.23

A new paradigm for treatment of vascular disease in the elderly <img style="float: left; margin-left: 10px; margin-right: 10px;" src="ArticleFile.do?id=11809854" width="237" height="341" />
A research team of Professor Sungyoung Kim from Konkuk University’s Medical School stated on the 21st that they have established a primary gene expression map that controls the aging of vascular endothelial cells.
The research using its self-developed artificial intelligence algorithms is being evaluated as suggesting the possibility of opening a new paradigm for treatment of vascular disease in the elderly by discovering key factors and biological pathways of vascular aging. It was published online in the lastest issue of ARR (Aging Res. Rev., IF:10.62), the world’s most authoritative journal in the field of aging, and was listed for ‘high impact journal’ selected by POSTECH’s ‘Best Researchers of Korea (Hanbitsa)’.
There is a quote that says, ‘A man is as old as his arteries’, from Professor William O’Sler, founder of Johns Hopkins Hospital. Vascular aging has been known as a key factor for vascular disease in the elderly, however, it is still unclear how blood vessels age and the molecular biology of the disease works.
Vascular endothelial cells compose inner walls of blood vessels, and are known to play an essential role in vascular diseases such as arteriosclerosis and vascular restenosis.
Professor Kim’s research team has completed a unique transcriptonal map of vascular aging by using its own machine learning based meta-analytic algorithms (MAMA).
 <img style="margin-left: auto; display: block; margin-right: auto;" alt="" src="ArticleFile.do?id=11809855" width="640" height="336" />　　　　　　　　　　　　　　　　　　　　　　　 Meta-analysis is a statistical technique which integrates data from independent yet similar studies to evaluate consistency of results and increase statistical accuracy and verification. It also produces estimates of the effectiveness of other important outcome variables that individual studies have overlooked.
The research team combined individual bio-path-based machine learning algorithms with meta-analysis, and developed a new type of artificial intelligence meta-analytic algorithm with greater consistency. Then, the team has newly found out 400 differentiating genes related to vascular aging and 36 key genes related to biological pathways.
In particular, the research team revealed that the enzyme PHGDH involved in metabolism of serine amino acid biosynthesis, a key metabolic pathway for single carbon metabolism, plays a crucial role in aging of vascular endothelial cells. PHGDH, as committed step, is a key pathway of metabolic control, and concerns the irreversible enzyme reaction at the branch of metabolism. Single carbon metabolism causes changes in biosynthesis of lipids, nucleic acids, proteins and various metabolic changes as well as various metabolic changes in our body including redox status and substrate for methylation reactions.
Professor Kim said, “With a number of anti-cancer drugs being actively researched for single-carbon metabolism, these new findings are expected to provide an important clue to control vascular disease in the elderly with current clinical drugs.”


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