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Quantitative Aggregation of Microbiome Sequencing Data Provides Insights into the Associations between the Skin Microbiome and Psoriasis.
Chan, Alfred A; Tran, Patrick T; Lee, Delphine J.
Affiliation
  • Chan AA; The Lundquist Institute, Torrance, California, USA.
  • Tran PT; Division of Dermatology, Harbor-UCLA Medical Center, Torrance, California, USA.
  • Lee DJ; The Lundquist Institute, Torrance, California, USA.
JID Innov ; 4(1): 100249, 2024 Jan.
Article in En | MEDLINE | ID: mdl-38282647
ABSTRACT
Although prior studies have reported distinct skin microbiome profiles associated with psoriasis, differences in methods and analyses limit generalizable conclusions. Individual studies have actually reported conflicting findings; for example, Propionibacterium and Staphylococcus have been significantly associated with both psoriatic lesions and healthy skin. Qualitative reviews have attempted to summarize this body of work, but there is great variability across the studies' findings and methods. To better unify these data, we created a meta-analysis of all publicly available datasets by utilizing a uniform bioinformatics pipeline and reference database to investigate associations of the skin microbiome in psoriasis. A total of 977 skin swab samples (341 lesional, 295 nonlesional, and 341 healthy) from 6 studies were analyzed. The aggregated analysis revealed a higher relative abundance of microorganisms, including Staphylococcus aureus and Corynebacterium simulans, among others, from patients with psoriasis than those from healthy swab samples; in addition, Cutibacterium acnes, Lawsonella unclassified, and S warneri were significantly higher in healthy samples. Furthermore, comparison of functional pathways predicted from 16S gene markers showed that L-ornithine biosynthesis and L-histidine biosynthesis were lower in psoriatic lesions than in healthy controls. Taken together, this meta-analysis allows for a more generalizable association between the skin microbiome and psoriasis.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research / Risk_factors_studies / Systematic_reviews Language: En Journal: JID Innov Year: 2024 Document type: Article Affiliation country: United States Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research / Risk_factors_studies / Systematic_reviews Language: En Journal: JID Innov Year: 2024 Document type: Article Affiliation country: United States Country of publication: Netherlands