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      Call for Papers: Digital Platforms and Artificial Intelligence in Dementia

      Submit here by August 31, 2025

      About Dementia and Geriatric Cognitive Disorders: 1.9 Impact Factor I 5.3 CiteScore I 0.781 Scimago Journal & Country Rank (SJR)

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      Rare MED12L Variants Are Associated with Susceptibility to Guttate Psoriasis in the Han Chinese Population

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          Abstract

          Introduction: According to the common disease/rare variant hypothesis, it is important to study the role of rare variants in complex diseases. The association of rare variants with psoriasis has been demonstrated, but the association between rare variants and specific clinical subtypes of psoriasis has not been investigated. Methods: Gene-based and gene-level meta-analyses were performed on data extracted from our previous study data sets (2,483 patients with guttate psoriasis and 8,292 patients with non-guttate psoriasis) for genotyping. Then, haplotype analysis was performed for rare loss-of-function variants located in MED12L, and protein function prediction was performed for MED12L. Gene-based analysis at each stage had a moderate significance threshold ( p < 0.05). A χ 2 test was then conducted on the three potential genes, and the merged gene-based analysis was used to confirm the results. We also conducted association analysis and meta-analysis for functional variants located on the identified gene. Results: Through these gene-level analyses, we determined that MED12L is a guttate psoriasis susceptibility gene ( p = 9.99 × 10 −5), and the single-nucleotide polymorphism with the strongest association was rs199780529 ( p _combine = 1 × 10 −3, p _meta = 2 × 10 −3). Conclusions: In our study, a guttate psoriasis-specific subtype-associated susceptibility gene was confirmed in a Chinese Han population. These findings contribute to a better genetic understanding of different subtypes of psoriasis.

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          Most cited references32

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          Is Open Access

          ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

          High-throughput sequencing platforms are generating massive amounts of genetic variation data for diverse genomes, but it remains a challenge to pinpoint a small subset of functionally important variants. To fill these unmet needs, we developed the ANNOVAR tool to annotate single nucleotide variants (SNVs) and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP. ANNOVAR can utilize annotation databases from the UCSC Genome Browser or any annotation data set conforming to Generic Feature Format version 3 (GFF3). We also illustrate a ‘variants reduction’ protocol on 4.7 million SNVs and indels from a human genome, including two causal mutations for Miller syndrome, a rare recessive disease. Through a stepwise procedure, we excluded variants that are unlikely to be causal, and identified 20 candidate genes including the causal gene. Using a desktop computer, ANNOVAR requires ∼4 min to perform gene-based annotation and ∼15 min to perform variants reduction on 4.7 million variants, making it practical to handle hundreds of human genomes in a day. ANNOVAR is freely available at http://www.openbioinformatics.org/annovar/ .
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            Is Open Access

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

            Summary: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: goncalo@umich.edu
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              An Expanded View of Complex Traits: From Polygenic to Omnigenic

              A central goal of genetics is to understand the links between genetic variation and disease. Intuitively, one might expect disease-causing variants to cluster into key pathways that drive disease etiology. But for complex traits, association signals tend to be spread across most of the genome-including near many genes without an obvious connection to disease. We propose that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways. We refer to this hypothesis as an "omnigenic" model.

                Author and article information

                Journal
                DRM
                Dermatology
                10.1159/issn.1018-8665
                Dermatology
                Dermatology
                S. Karger AG
                1018-8665
                1421-9832
                2024
                August 2024
                10 May 2024
                : 240
                : 4
                : 606-614
                Affiliations
                [a ]Department of Dermatology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
                [b ]Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China
                [c ]Anhui Province Laboratory of Inflammation and Immune Mediated Diseases, Hefei, China
                [d ]Anhui Provincial Institute of Translational Medicine, Hefei, China
                [e ]First Clinical Medical College, Anhui Medical University, Hefei, China
                [f ]Second Clinical Medical College, Anhui Medical University, Hefei, China
                [g ]School of Life Science, Shandong University, Qingdao, China
                Author notes
                *Mengyun Chen, chenmengyun888@163.com, Xiaodong Zheng, zhengxiaodong.1234@163.com
                Article
                538805 Dermatology 2024;240:606–614
                10.1159/000538805
                38735287
                8f717bd4-4ab5-445a-9087-445afda46d1f
                © 2024 S. Karger AG, Basel
                History
                : 09 October 2022
                : 08 April 2024
                Page count
                Figures: 2, Tables: 4, Pages: 9
                Funding
                This work was supported by the Youth Program of the First Affiliated Hospital of Anhui Medical University [Grant No. 293191] and the fund for College Students’ Innovative Entrepreneurial Training Plan Program [Grant No. S202110366010].
                Categories
                Genetics – Research Article

                Medicine
                Guttate psoriasis,Gene-based analysis,Rare variant
                Medicine
                Guttate psoriasis, Gene-based analysis, Rare variant

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