Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci

Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo

Epigenome-wide association data implicates DNA methylation-mediated genetic risk in psoriasis

Abstract Background Psoriasis is a chronic inflammatory skin disease characterized by epidermal hyperproliferation and altered keratinocyte differentiation and inflammation and is caused by the interplay of genetic and environmental factors. Previous studies have revealed that DNA methylation (DNAm) and genetic makers are closely associated with psoriasis, and strong evidences have shown that DNAm can be controlled by genetic factors, which attracted us to evaluate the relationship among DNAm, genetic makers, and disease status. Methods We utilized the genome-wide methylation data of psoriatic skin (PP, N = 114) and unaffected control skin (NN, N = 62) tissue samples in our previous study, and we performed whole-genome genotyping with peripheral blood of the same samples to evaluate the underlying genetic effect on skin DNA methylation. Causal inference test (CIT) was used to assess whether DNAm regulate genetic variation and gain a better understanding of the epigenetic basis of psoriasis susceptibility. Results We identified 129 SNP-CpG pairs achieving the significant association threshold, which constituted 28 unique methylation quantitative trait loci (MethQTL) and 34 unique CpGs. There are 18 SNPs were associated with psoriasis at a Bonferoni-corrected P < 0.05, and these 18 SNPs formed 93 SNP-CpG pairs with 17 unique CpG sites. We found that 11 of 93 SNP-CpG pairs, composed of 5 unique SNPs and 3 CpG sites, presented a methylation-mediated relationship between SNPs and psoriasis. The 3 CpG sites were located on the body of C1orf106, the TSS1500 promoter region of DMBX1 and the body of SIK3. Conclusions This study revealed that DNAm of some genes can be controlled by genetic factors and also mediate risk variation for psoriasis in Chinese Han population and provided novel molecular insights into the pathogenesis of psoriasis

A Comparative Study on the Mathematic Models for the Ignition of Titanium Alloy in Oxygen-Enriched Environment

Metallic materials are always suffered from the risk of combustion when serviced under some extreme conditions such as high temperature, oxygen-enriched enrichment, and high-speed friction. Although different mathematic models have been proposed but it is still a challenge for accurately describing the ignition conditions of metals under the extreme conditions, which is of great significance for the safety-use of materials. In this paper, the mathematic models based on Semenov and Frank-Kamenetskii theory were introduced into describing the effects of size, oxygen concentration, and oxygen pressure on the ignition temperature and critical oxygen pressure of TC17 alloy. The results showed that the critical oxygen pressure of TC17 alloy increased with the increase of size, which was fitted well with the Frank-Kamenetskii model. As a comparison, the critical oxygen pressure was size independent in the Semenov model, which was inconsistent with the experimental data. For the Frank-Kamenetskii model, the fitting results showed that the activation energy, reaction order, as well as the adsorption coefficient of TC17 alloy were determined to be 99.23 kJ/mol, 1.69, and 4.01 MPa&minus;1.69 respectively. Based on above, the ignition temperature of TC17 samples with different sizes were predicted well by the Frank-Kamenetskii model with the relative error within 3.58%, which could be suitable for describing the critical ignition conditions of bulk metallic materials under complex environment

Genotype combination contributes to psoriasis: An exhaustive algorithm perspective

<div><p>Researchers have learned that nearly all conditions and diseases have a genetic component. With the benefit of technological advances, many single-nucleotide polymorphisms (SNPs) have been found to be associated with the risk of complex disorders by using genome wide association studies (GWASs). Disease-associated SNPs are sometimes shared by healthy controls and cannot clearly distinguish affected individuals from unaffected ones. The combined effects of multiple independent SNPs contribute to the disease process, but revealing the relationship between genotype and phenotype based on the combinations remains a great challenge. In this study, by considering the disease prevalence rate, we conducted an exhaustive process to identify whether a genotype combination pattern would have a decisive effect on complex disorders. Based on genotype data for 68 reported SNPs in 8,372 psoriasis patients and 8,510 healthy controls, we found that putative causal genotype combination patterns (CGCPs) were only present in psoriasis patients, not in healthy subjects. These results suggested that psoriasis might be contributed by combined genotypes, complementing the traditional modest susceptibility of a single variant in a single gene for a complex disease. This work is the first systematic study to analyze genotype combinations based on the reported susceptibility genes, considering each individual among the cases and controls from the Chinese population, and could potentially advance disease-gene mapping and precision medicine due to the causality relationship between the candidate CGCPs and complex diseases.</p></div

Additional file 2: of Epigenome-wide association data implicates DNA methylation-mediated genetic risk in psoriasis

Figure S1. Genomic annotation for methylation probes. Refseq genes annotations were from the University of California, Santa Cruz (UCSC) hg18 reference genome [National Center for Biotechnology Information (NCBI) Reference Sequence Database Release 37]. CpG sites located in or near Refseq genes are separated into TSS1500 (1500 bp upstream of the transcription start site), TSS200, 5′ UTR, first exon, gene body, and 3′ UTR regions. Intergenic probes refer to methylation sites not mapping to any of the other categories. The ambiguous regions include sites that fell into two or more different categories. The promoter region includes methylation sites located in TSS1500, TSS200, 5′ UTR, and first exon. (DOC 92 kb

The toppest candidate CGCP results for three, four and five SNPs and corresponding number of psoriasis patients.

<p>The toppest candidate CGCP results for three, four and five SNPs and corresponding number of psoriasis patients.</p

The 51 SNPs and alleles associated with psoriasis in the autosomal chromosome.

<p>The outmost lines with different colors represent chromosomes labled by 1–22, and ribbon colors in chromosomes assigned to Giemsa stain based on the color scheme of the UCSC genome browser represent chromosome bands.</p

Distribution of permuted number of patients with the candidate CGCP in every 1000 cases.

<p>The arrow shows the observed number of individuals with the toppest candidate CGCP for three (A), four (B) and five (C) SNPs in the 1000 cases.</p

The summary information of samples.

<p>The summary information of samples.</p