Literature DB >> 36261456

Host genetic factors related to innate immunity, environmental sensing and cellular functions are associated with human skin microbiota.

Andre Franke1, Stephan Weidinger2, Malte Christoph Rühlemann3, Lucas Moitinho-Silva3,4, Frauke Degenhardt3, Elke Rodriguez4, Hila Emmert4, Simonas Juzenas3,5, Lena Möbus4, Florian Uellendahl-Werth3, Nicole Sander4, Hansjörg Baurecht6, Lukas Tittmann7, Wolfgang Lieb8, Christian Gieger9,10, Annette Peters9, David Ellinghaus3, Corinna Bang3.   

Abstract

Despite the increasing knowledge about factors shaping the human microbiome, the host genetic factors that modulate the skin-microbiome interactions are still largely understudied. This contrasts with recent efforts to characterize host genes that influence the gut microbiota. Here, we investigated the effect of genetics on skin microbiota across three different skin microenvironments through meta-analyses of genome-wide association studies (GWAS) of two population-based German cohorts. We identified 23 genome-wide significant loci harboring 30 candidate genes involved in innate immune signaling, environmental sensing, cell differentiation, proliferation and fibroblast activity. However, no locus passed the strict threshold for study-wide significance (P < 6.3 × 10-10 for 80 features included in the analysis). Mendelian randomization (MR) analysis indicated the influence of staphylococci on eczema/dermatitis and suggested modulating effects of the microbiota on other skin diseases. Finally, transcriptional profiles of keratinocytes significantly changed after in vitro co-culturing with Staphylococcus epidermidis, chosen as a representative of skin commensals. Seven candidate genes from the GWAS were found overlapping with differential expression in the co-culturing experiments, warranting further research of the skin commensal and host genetic makeup interaction.
© 2022. The Author(s).

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Year:  2022        PMID: 36261456      PMCID: PMC9582029          DOI: 10.1038/s41467-022-33906-5

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   17.694


  70 in total

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Authors:  R Holle; M Happich; H Löwel; H E Wichmann
Journal:  Gesundheitswesen       Date:  2005-08

3.  Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

Authors:  Qiong Wang; George M Garrity; James M Tiedje; James R Cole
Journal:  Appl Environ Microbiol       Date:  2007-06-22       Impact factor: 4.792

4.  PLINK: a tool set for whole-genome association and population-based linkage analyses.

Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
Journal:  Am J Hum Genet       Date:  2007-07-25       Impact factor: 11.025

5.  Population-level analysis of gut microbiome variation.

Authors:  Gwen Falony; Marie Joossens; Sara Vieira-Silva; Jun Wang; Youssef Darzi; Karoline Faust; Alexander Kurilshikov; Marc Jan Bonder; Mireia Valles-Colomer; Doris Vandeputte; Raul Y Tito; Samuel Chaffron; Leen Rymenans; Chloë Verspecht; Lise De Sutter; Gipsi Lima-Mendez; Kevin D'hoe; Karl Jonckheere; Daniel Homola; Roberto Garcia; Ettje F Tigchelaar; Linda Eeckhaudt; Jingyuan Fu; Liesbet Henckaerts; Alexandra Zhernakova; Cisca Wijmenga; Jeroen Raes
Journal:  Science       Date:  2016-04-28       Impact factor: 47.728

6.  Skin microbiota analysis in human 3D skin models-"Free your mice".

Authors:  Hila Emmert; Franziska Rademacher; Regine Gläser; Jürgen Harder
Journal:  Exp Dermatol       Date:  2020-08-27       Impact factor: 3.960

7.  The nf-core framework for community-curated bioinformatics pipelines.

Authors:  Philip A Ewels; Alexander Peltzer; Sven Fillinger; Harshil Patel; Johannes Alneberg; Andreas Wilm; Maxime Ulysse Garcia; Paolo Di Tommaso; Sven Nahnsen
Journal:  Nat Biotechnol       Date:  2020-03       Impact factor: 54.908

8.  METAL: fast and efficient meta-analysis of genomewide association scans.

Authors:  Cristen J Willer; Yun Li; Gonçalo R Abecasis
Journal:  Bioinformatics       Date:  2010-07-08       Impact factor: 6.937

9.  Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity.

Authors:  Alexandra Zhernakova; Alexander Kurilshikov; Marc Jan Bonder; Ettje F Tigchelaar; Melanie Schirmer; Tommi Vatanen; Zlatan Mujagic; Arnau Vich Vila; Gwen Falony; Sara Vieira-Silva; Jun Wang; Floris Imhann; Eelke Brandsma; Soesma A Jankipersadsing; Marie Joossens; Maria Carmen Cenit; Patrick Deelen; Morris A Swertz; Rinse K Weersma; Edith J M Feskens; Mihai G Netea; Dirk Gevers; Daisy Jonkers; Lude Franke; Yurii S Aulchenko; Curtis Huttenhower; Jeroen Raes; Marten H Hofker; Ramnik J Xavier; Cisca Wijmenga; Jingyuan Fu
Journal:  Science       Date:  2016-04-28       Impact factor: 47.728

10.  FINEMAP: efficient variable selection using summary data from genome-wide association studies.

Authors:  Christian Benner; Chris C A Spencer; Aki S Havulinna; Veikko Salomaa; Samuli Ripatti; Matti Pirinen
Journal:  Bioinformatics       Date:  2016-01-14       Impact factor: 6.937

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