IGSF23

Last update 08 May 2025

Basic Info

Synonyms

IGSF23, immunoglobulin superfamily member 23

Introduction

May be involved in osteoclast differentiation.

100 Clinical Results associated with IGSF23

100 Translational Medicine associated with IGSF23

0 Patents (Medical) associated with IGSF23

Literatures (Medical) associated with IGSF23

01 Jul 2024·iScience

The genome of African manatee Trichechus senegalensis reveals secondary adaptation to the aquatic environment

Article

Author: Guan, Dengfeng ; Huang, Xin ; Zhou, Wenliang ; Wei, Fuwen ; Huang, Guangping ; Fan, Huizhong ; Zhang, Delu ; Dong, Guixin

Sirenians exhibit unique aquatic adaptations, showcasing both convergent adaptive features shared with cetaceans and unique characteristics such as cold sensitivity and dense bones. Here, we report a chromosome-level genome of the African manatee (Trichechus senegalensis) with high continuity, completeness, and accuracy. We found that genes associated with osteopetrosis have undergone positive selection (CSF1R and LRRK1) or pseudogenized (FAM111A and IGSF23) in the African manatee, potentially contributing to the dense bone formation. The loss of KCNK18 may have increased their sensitivity to cold water temperatures. Moreover, we identified convergent evolutionary signatures in 392 genes among fully aquatic mammals, primarily enriched in skin or skeletal system development and circadian rhythm, which contributed to the transition from terrestrial to fully aquatic lifestyles. The African manatee currently possesses a small effective population size and low genome-wide heterozygosity. Overall, our study provides genetic resources for understanding the evolutionary characteristics and conservation efforts of this species.

01 Dec 2021·Alzheimer's & dementia : the journal of the Alzheimer's Association

Copy number variation (CNV) identification and association study on 3,928 Alzheimer's disease whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP).

Article

Author: Wang, Li-San ; Tzeng, Jung-Ying ; Schellenberg, Gerard D ; Chou, Yi-Fan ; Brucker, Amanda ; Lee, Wan-Ping ; Kuzma, Amanda B ; Tucci, Albert A ; Conery, Mitchell ; Leung, Yuk Yee ; Lu, Wenbin ; Valladares, Otto

BACKGROUNDEstimation of heritability of Alzheimer's Disease (AD) ranges from 49-79%, but the conventional single nucleotide variants (SNVs) identified to date account for <50% of the AD heritability. The involvement of genetic variants, such as SNVs and copy number variations (CNVs), has been proposed to explain part of the missing heritability.METHODTo accelerate AD genetic discovery, the Alzheimer's Disease Sequencing Project (ADSP) sequenced cases and cognitively normal elder controls from multiple ethnic groups. Leveraging this large-scale Whole Genome Sequence (WGS) collection, we could detect and conduct AD genetic analyses in full-spectrum of CNVs (small or large, common or rare, and coding or non-coding in genomic regions). We developed a bioinformatics pipeline consisting of four steps. First, we applied three calling algorithms, CNVnator, JAX-CNV, and Smoove, on each sample. Results of each tool were then merged by Svimmer. Second, we employed GraphTyper for genotyping. GraphTyper is a graph-pangenome-based method that may mitigate bias of human references. Finally, we resolved issues of multiple CNVs overlapping in a region by bedtools. Once the CNV callset was obtained, we conducted an association study to identify CNV regions that contribute to AD. We consider conventional association methods as well as a new developed CNV-curve-centric strategy which models CNVs as piecewise constant curves to assess the CNV effect on AD.RESULTFor each sample, we identified an average of 7,959 CNVs by three algorithms. After merging CNVs of all samples, we obtained 56,316 deletions and 16,390 duplications for GraphTyper joint genotyping. The preliminary results of PLINK permutation-based test on the chromosome 19 indicated significant CNVs (p-value < 0.05 after adjusting for multiple tests) on genes UNC13A, IGSF23, KMT2B, LIN37, PSENEN, IGFLR1, and U2AF1L4. UNC13A, KMT2B, and PSENEN have been discovered to be associated in frontotemporal dementia, dystonia, and AD. Further validations of those CNVs are necessary.CONCLUSIONWe developed a scalable CNV detection pipeline and applied it to 3,928 ADSP WGS samples. The preliminary results of the association study validate some known AD, dementia, and dystonia genes. To the best of our knowledge, this is the first large-scale CNV investigation of AD using WGS data.

01 Jan 2020·International Journal of Medical SciencesQ3 · MEDICINE

Multi‐omics analysis of tumor mutational burden combined with prognostic assessment in epithelial ovarian cancer based on TCGA database

Q3 · MEDICINE

ArticleOA

Author: Sun, Rui ; Liu, Jinhui ; Cheng, Wenjun ; Li, Siyue ; Xu, Wei

Background: Tumor mutation burden (TMB) is considered as a novel biomarker of response to immunotherapy and correlated with survival outcomes in various malignancies. Here, TMB-related genes (TRGs) expression signatures were constructed to investigate the association between TMB and prognosis in epithelial ovarian cancer (EOC), and the potential mechanism in immunoregulation was also explored. Methods: Based on somatic mutation data of 436 EOC samples from The Cancer Genome Atlas database, we examined the relationship between TMB level and overall survival (OS), as well as disease-free survival (DFS). Next, the TRGs signatures were constructed and validated. Differential abundance of immune cell infiltration, expression levels of immunomodulators and functional enrichment in high- and low-risk groups were also analyzed. Results: Higher TMB level revealed better OS and DFS, and correlated with earlier clinical stages in EOCs (P = 2.796e-04). The OS-related prognostic model constructed based on seven TRGs (B3GALT1, LIN7B, ANGPT2, D2HGDH, TAF13, PFDN4 and DNAJC19) significantly stratified EOC patients into high- and low-risk groups (P < 0.001). The AUC values of the seven-gene prognostic signature at 1 year, 3 years, and 5 years were 0.703, 0.758 and 0.777. While the DFS-related prognostic model was constructed based on the 4 TRGs (LPIN3, PXYLP1, IGSF23 and B3GALT1), with AUCs of 0.617, 0.756, and 0.731, respectively. Functional analysis indicated that immune-related pathways were enriched in low-risk groups. When considering the infiltration patterns of immune cells, we found higher proportions of follicular helper T (Tfh) cell and M1 macrophage, while lower infiltration of M0 macrophage in low-risk groups (P < 0.05). Accordingly, TMB levels of low-risk patients were significantly higher both in OS and DFS model (P < 0.01). Conclusions: Our TRGs-based models are reliable predictive tools for OS and DFS. High TMB may confer with an immunogenic microenvironment and predict favorable outcomes in EOCs.

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IGSF23

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