Gut Microbial Dysbiosis and Plasma Metabolic Profile in Individuals With Vitiligo

被引:40
作者
Ni, Qingrong [1 ]
Ye, Zhubiao [1 ]
Wang, Yinghan [1 ]
Chen, Jianru [1 ]
Zhang, Weigang [1 ]
Ma, Cuiling [1 ]
Li, Kai [1 ]
Liu, Yu [1 ]
Liu, Ling [1 ]
Han, Zheyi [2 ,3 ]
Gao, Tianwen [1 ]
Jian, Zhe [1 ]
Li, Shuli [1 ]
Li, Chunying [1 ]
机构
[1] Fourth Mil Med Univ, Xijing Hosp, Dept Dermatol, Xian, Peoples R China
[2] Fourth Mil Med Univ, Xijing Hosp, Dept Gastroenterol, Xian, Peoples R China
[3] Natl Clin Res Ctr Digest Dis, Xian, Peoples R China
基金
中国国家自然科学基金;
关键词
vitiligo; gut microbiome; 16S rRNA sequence; serum metabolomic; gut-skin axis; DISEASE-ACTIVITY; T-CELLS; SERUM; STRESS; LIFE;
D O I
10.3389/fmicb.2020.592248
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Autoimmune diseases are increasingly linked to aberrant gut microbiome and relevant metabolites. However, the association between vitiligo and the gut microbiome remains to be elucidated. Thus, we conducted a case-control study through 16S rRNA sequencing and serum untargeted-metabolomic profiling based on 30 vitiligo patients and 30 matched healthy controls. In vitiligo patients, the microbial composition was distinct from that of healthy controls according to the analysis on alpha- and beta-diversity (P < 0.05), with a characteristic decreased Bacteroidetes: Firmicutes ratio. Meanwhile, the levels of 23 serum metabolites (including taurochenodeoxycholate and L-NG-monomethyl-arginine) in the vitiligo patients were different from those in the healthy individuals and showed significant correlations with some microbial markers. We found that Corynebacterium 1, Ruminococcus 2, Jeotgalibaca and Psychrobacter were correlated significantly with disease duration and serum IL-1 beta level in vitiligo patients. And Psychrobacter was identified as the most predictive features for vitiligo by machine learning analysis ("importance" = 0.0236). Finally, combining multi-omics data and joint prediction models with accuracies up to 0.929 were established with dominant contribution of Corynebacterium 1 and Psychrobacter. Our findings replenished the previously unknown relationship between gut dysbiosis and vitiligo circulating metabolome and enrolled the gut-skin axis into the understanding of vitiligo pathogenesis.
引用
收藏
页数:13
相关论文
共 64 条
[1]   The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update [J].
Afgan, Enis ;
Baker, Dannon ;
Batut, Berenice ;
van den Beek, Marius ;
Bouvier, Dave ;
Cech, Martin ;
Chilton, John ;
Clements, Dave ;
Coraor, Nate ;
Gruening, Bjoern A. ;
Guerler, Aysam ;
Hillman-Jackson, Jennifer ;
Hiltemann, Saskia ;
Jalili, Vahid ;
Rasche, Helena ;
Soranzo, Nicola ;
Goecks, Jeremy ;
Taylor, James ;
Nekrutenko, Anton ;
Blankenberg, Daniel .
NUCLEIC ACIDS RESEARCH, 2018, 46 (W1) :W537-W544
[2]  
Amir A., 2017, MSYSTEMS, V2, DOI DOI 10.1128/MSYSTEMS.00191-16
[3]  
Anderson MJ, 2001, AUSTRAL ECOL, V26, P32, DOI 10.1111/j.1442-9993.2001.01070.pp.x
[4]  
[Anonymous], 1991, NUCL ACID TECHNIQUES
[5]   Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data [J].
Asshauer, Kathrin P. ;
Wemheuer, Bernd ;
Daniel, Rolf ;
Meinicke, Peter .
BIOINFORMATICS, 2015, 31 (17) :2882-2884
[6]   Factors affecting quality of life in patients with vitiligo: a nationwide study [J].
Bae, J. M. ;
Lee, S. C. ;
Kim, T. H. ;
Yeom, S. D. ;
Shin, J. H. ;
Lee, W. J. ;
Lee, M. -H. ;
Lee, A. -Y. ;
Kim, K. H. ;
Kim, M. B. ;
Park, C. J. ;
Lee, S. H. ;
Kim, D. H. ;
Lee, H. J. ;
Lee, D. Y. ;
Choi, C. W. ;
Kim, Y. C. ;
Kang, H. Y. ;
Haw, S. ;
Lee, Y. B. ;
Yun, S. J. ;
Yun, S. -K. ;
Hong, S. P. ;
Lee, Y. ;
Kim, H. J. ;
Choi, G. S. .
BRITISH JOURNAL OF DERMATOLOGY, 2018, 178 (01) :238-244
[7]  
Bamola V. Deepak, 2017, Microbial Ecology in Health and Disease, V28, P1322447, DOI 10.1080/16512235.2017.1322447
[8]   Increased systemic and epidermal levels of IL-17A and IL-1β promotes progression of non-segmental vitiligo [J].
Bhardwaj, Supriya ;
Rani, Seema ;
Srivastava, Niharika ;
Kumar, Ravinder ;
Parsad, Davinder .
CYTOKINE, 2017, 91 :153-161
[9]  
Bokulich N.A., 2018, J Open Res Softw, V3, P934
[10]   Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 [J].
Bolyen, Evan ;
Rideout, Jai Ram ;
Dillon, Matthew R. ;
Bokulich, NicholasA. ;
Abnet, Christian C. ;
Al-Ghalith, Gabriel A. ;
Alexander, Harriet ;
Alm, Eric J. ;
Arumugam, Manimozhiyan ;
Asnicar, Francesco ;
Bai, Yang ;
Bisanz, Jordan E. ;
Bittinger, Kyle ;
Brejnrod, Asker ;
Brislawn, Colin J. ;
Brown, C. Titus ;
Callahan, Benjamin J. ;
Caraballo-Rodriguez, Andres Mauricio ;
Chase, John ;
Cope, Emily K. ;
Da Silva, Ricardo ;
Diener, Christian ;
Dorrestein, Pieter C. ;
Douglas, Gavin M. ;
Durall, Daniel M. ;
Duvallet, Claire ;
Edwardson, Christian F. ;
Ernst, Madeleine ;
Estaki, Mehrbod ;
Fouquier, Jennifer ;
Gauglitz, Julia M. ;
Gibbons, Sean M. ;
Gibson, Deanna L. ;
Gonzalez, Antonio ;
Gorlick, Kestrel ;
Guo, Jiarong ;
Hillmann, Benjamin ;
Holmes, Susan ;
Holste, Hannes ;
Huttenhower, Curtis ;
Huttley, Gavin A. ;
Janssen, Stefan ;
Jarmusch, Alan K. ;
Jiang, Lingjing ;
Kaehler, Benjamin D. ;
Bin Kang, Kyo ;
Keefe, Christopher R. ;
Keim, Paul ;
Kelley, Scott T. ;
Knights, Dan .
NATURE BIOTECHNOLOGY, 2019, 37 (08) :852-857