Hidden Links Between Skin Microbiome and Skin Imaging Phenome  

作　　者：Mingyue Cheng Hong Zhou Haobo Zhang Xinchao Zhang Shuting Zhang Hong Bai Yugo Zha Dan Luo Dan Chen Siyuan Chen Kang Ning Wei Liu 

机构地区：[1]College of Life Science and Technology,Huazhong University of Science and Technology,Wuhan 430074,China [2]National Engineering Research Center for Nanomedicine,Huazhong University of Science and Technology,Wuhan 430074,China [3]Key Laboratory of Molecular Biophysics of the Ministry of Education,Hubei Key Laboratory of Bioinformatics and Molecular Imaging,Center of Artificial Intelligence Biology,Department of Bioinformatics and Systems Biology,Huazhong University of Science and Technology,Wuhan 430074,China [4]Research Institute for Biomaterials,Tech Institute for Advanced Materials,College of Materials Science and Engineering,Suqian Advanced Materials Industry Technology Innovation Center,NJTech-BARTY Joint Research Center for Innovative Medical Technology,Nanjing Tech University,Nanjing 211816,China

出　　处：《Genomics, Proteomics & Bioinformatics》2024年第4期47-58,共12页基因组蛋白质组与生物信息学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.32071465,31871334,and 31671374);the National Key R&D Program of China(Grant No.2018YFC0910502);Yuhao Zhang(Huazhong University of Science and Technology,China)to improve the analysis of this study。

摘　　要：Despite the skin microbiome has been linked to skin health and diseases,its role in modulating human skin appearance remains understudied.Using a total of 1244 face imaging phenomes and 246 cheek metagenomes,we first established three skin age indices by machine learning,including skin phenotype age(SPA),skin microbiota age(SMA),and skin integration age(SIA)as surrogates of phenotypic aging,microbial aging,and their combination,respectively.Moreover,we found that besides aging and gender as intrinsic factors,skin microbiome might also play a role in shaping skin imaging phenotypes(SIPs).Skin taxonomic and functionalαdiversity was positively linked to melanin,pore,pigment,and ultraviolet spot levels,but negatively linked to sebum,lightening,and porphyrin levels.Furthermore,certain species were correlated with specific SIPs,such as sebum and lightening levels negatively correlated with Corynebacterium matruchotii,Staphylococcus capitis,and Streptococcus sanguinis.Notably,we demonstrated skin microbial potential in predicting SIPs,among which the lightening level presented the least error of 1.8%.Lastly,we provided a reservoir of potential mechanisms through which skin microbiome adjusted the SIPs,including the modulation of pore,wrinkle,and sebum levels by cobalamin and heme synthesis pathways,predominantly driven by Cutibacterium acnes.This pioneering study unveils the paradigm for the hidden links between skin microbiome and skin imaging phenome,providing novel insights into how skin microbiome shapes skin appearance and its healthy aging.

关 键 词：Skin phenome Skin microbiome METAGENOME Machine learning Imaging. 

分 类 号：R75[医药卫生—皮肤病学与性病学]