Literature DB >> 22243446

The use of the twin model to investigate the genetics and epigenetics of skin diseases with genomic, transcriptomic and methylation data.

V Bataille1, M Lens, T D Spector.   

Abstract

Twins have always fascinated medical research even before the discovery of DNA and the understanding of the differences between identical and non-identical twins. Dermatology with the benefit of being able to visualize phenotypes was one of the first specialities reporting on the fascinating concordance in identical (MZ) twins in the 1920's. Over the last 20 years, the heritability of skin diseases using twins has been clearly demonstrated, across a wide variety of traits including melanoma, polymorphic light eruption, psoriasis, eczema and acne. Other rarer diseases have also been shown to have a significant genetic basis such as lupus, sarcoidosis and lichen sclerosus. Following evidence of heritability for many skin disease the next step was Genome-Wide Association Studies (GWAS) which are uncovering new genes in large twin cohorts. The twin model is also ideal for the new field of epigenetics, investigating subtle differences in DNA methylation within discordant MZ pairs for a disease, as well as differences in CNVs. Twins are also valuable for examining differences in gene function via RNA expression in twins discordant for a skin trait or disease.
© 2012 The Authors. Journal of the European Academy of Dermatology and Venereology © 2012 European Academy of Dermatology and Venereology.

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Mesh:

Year:  2012        PMID: 22243446     DOI: 10.1111/j.1468-3083.2011.04444.x

Source DB:  PubMed          Journal:  J Eur Acad Dermatol Venereol        ISSN: 0926-9959            Impact factor:   6.166


  15 in total

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3.  Genome-wide association studies with metabolomics.

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4.  DNA methylation of the filaggrin gene adds to the risk of eczema associated with loss-of-function variants.

Authors:  A H Ziyab; W Karmaus; J W Holloway; H Zhang; S Ewart; S H Arshad
Journal:  J Eur Acad Dermatol Venereol       Date:  2012-09-25       Impact factor: 6.166

Review 5.  Putting together the psoriasis puzzle: an update on developing targeted therapies.

Authors:  Leanne M Johnson-Huang; Michelle A Lowes; James G Krueger
Journal:  Dis Model Mech       Date:  2012-07       Impact factor: 5.758

6.  Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis.

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Journal:  Nat Genet       Date:  2015-10-19       Impact factor: 38.330

7.  Polygenic prediction of atopic dermatitis improves with atopic training and filaggrin factors.

Authors:  Christopher H Arehart; Michelle Daya; Monica Campbell; Meher Preethi Boorgula; Nicholas Rafaels; Sameer Chavan; Gloria David; Jon Hanifin; Mark K Slifka; Richard L Gallo; Tissa Hata; Lynda C Schneider; Amy S Paller; Peck Y Ong; Jonathan M Spergel; Emma Guttman-Yassky; Donald Y M Leung; Lisa A Beck; Christopher R Gignoux; Rasika A Mathias; Kathleen C Barnes
Journal:  J Allergy Clin Immunol       Date:  2021-06-07       Impact factor: 10.793

Review 8.  Genetic dysbiosis: the role of microbial insults in chronic inflammatory diseases.

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9.  LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis.

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Journal:  Bioinformatics       Date:  2016-09-22       Impact factor: 6.937

10.  Combining CDKN1A gene expression and genome-wide SNPs in a twin cohort to gain insight into the heritability of individual radiosensitivity.

Authors:  Joanna Zyla; Sylwia Kabacik; Grainne O'Brien; Salma Wakil; Najla Al-Harbi; Jaakko Kaprio; Christophe Badie; Joanna Polanska; Ghazi Alsbeih
Journal:  Funct Integr Genomics       Date:  2019-01-31       Impact factor: 3.410

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