Ask about this productRelated genes to: SNTG1 antibody
- Gene:
- SNTG1 NIH gene
- Name:
- syntrophin gamma 1
- Previous symbol:
- -
- Synonyms:
- SYN4, G1SYN
- Chromosome:
- 8q11.21
- Locus Type:
- gene with protein product
- Date approved:
- 2000-10-20
- Date modifiied:
- 2016-12-13
Related products to: SNTG1 antibody
Related articles to: SNTG1 antibody
- Childhood obesity (OB) is influenced by complex gene-environmental interaction. While genetics of adult OB have been extensively studied, polygenic childhood OB in non-European populations is still underexplored. Furthermore, in a developing nation such as India, how the environmental component strongly modulated by the socioeconomic status (SES) shapes the genetic susceptibility is crucial to understand. - Source: PubMed
Publication date: 2025/02/25
Nair Janaki MChauhan GaneshPrasad GauriBandesh KhushdeepGiri Anil KChakraborty ShraddhaMarwaha Raman KMathur SandeepChoudhury DevapriyaTandon NikhilBasu AnalabhaBharadwaj Dwaipayan - Limited whole genome sequencing (WGS) studies in Asian populations result in a lack of representative reference panels, thus hindering the discovery of ancestry-specific variants. Here, we present the South and East Asian reference Database (SEAD) panel ( https://imputationserver.westlake.edu.cn/ ), which integrates WGS data for 11,067 individuals from various sources across 17 Asian countries. The SEAD panel, comprising 22,134 haplotypes and 88,294,957 variants, demonstrates improved imputation accuracy for South Asian populations compared to 1000 Genomes Project, TOPMed, and ChinaMAP panels, with a higher proportion of well-imputed rare variants. For East Asian populations, SEAD shows concordance comparable to ChinaMAP, but outperforming TOPMed. Additionally, we apply the SEAD panel to conduct a genome-wide association study for total hip (Hip) and femoral neck (FN) bone mineral density (BMD) traits in 5369 genotyped Chinese samples. The single-variant test suggests that rare variants near SNTG1 are associated with Hip BMD (rs60103302, MAF = 0.0092, P = 1.67 × 10), and variant-set analysis further supports the association (P = 9.08 × 10, P = 5.27 × 10). This association was not reported previously and can only be detected by using Asian reference panels. Preliminary in vitro experiments for one of the rare variants identified provide evidence that it upregulates SNTG1 expression, which could in turn inhibit the proliferation and differentiation of preosteoblasts. - Source: PubMed
Publication date: 2024/12/30
Yang Meng-YuanZhong Jia-DongLi XinTian GengBai Wei-YangFang Yi-HuQiu Mo-ChangYuan Cheng-DaYu Chun-FuLi NanYang Ji-JianLiu Yu-HengYu Shi-HuiZhao Wei-WeiLiu Jun-QuanSun YiCong Pei-KuanKhederzadeh SaberZhao Pian-PianQian YuGuan Peng-LinGu Jia-XuanGai Si-RuiYi Xiang-JiaoTao Jian-GuoChen XiangMiao Mao-MaoLei Lan-XinXu LinXie Shu-YangLi Jin-ChenGuo Ji-FengKarasik DavidYang LiuTang Bei-ShaHuang FeiZheng Hou-Feng - Hepatocellular carcinoma (HCC) is one of the most fatal malignancies. Early diagnosis of HCC is crucial in reducing the risk for mortality. This study analyzed a panel of nine fusion transcripts in serum samples from 61 patients with HCC and 75 patients with non-HCC conditions, using TaqMan real-time quantitative RT-PCR. Seven of the nine fusions frequently detected in patients with HCC included: MAN2A1-FER (100%), SLC45A2-AMACR (62.3%), ZMPSTE24-ZMYM4 (62.3%), PTEN-NOLC1 (57.4%), CCNH-C5orf30 (55.7%), STAMBPL1-FAS (26.2%), and PCMTD1-SNTG1 (16.4%). Machine-learning models were constructed based on serum fusion-gene levels to predict HCC in the training cohort, using the leave-one-out cross-validation approach. One machine-learning model, called the four fusion genes logistic regression model (MAN2A1-FER≤40, CCNH-C5orf30≤38, SLC45A2-AMACR≤41, and PTEN-NOLC1≤40), produced accuracies of 91.5% and 83.3% in the training and testing cohorts, respectively. When serum α-fetal protein level was incorporated into the machine-learning model, a two fusion gene (MAN2A1-FER≤40, CCNH-C5orf30≤38) + α-fetal protein logistic regression model was found to generate an accuracy of 94.8% in the training cohort. The same model resulted in 95% accuracy in both the testing and combined cohorts. Cancer treatment was associated with reduced levels of most of the serum fusion transcripts. Serum fusion-gene machine-learning models may serve as important tools in screening for HCC and in monitoring the impact of HCC treatment. - Source: PubMed
Publication date: 2024/03/25
Yu Yan-PingLiu SilviaGeller DavidLuo Jian-Hua - Research has shown epigenetic change via alternation of the methylation profile of human skeletal muscle DNA after Cardio-Pulmonary Bypass (CPB). In this study, we investigated the change in epigenome-wide DNA methylation profiles of porcine myocardium after ischemic insult in the setting of treatment with extracellular vesicle (EV) therapy in normal . high-fat diet (HFD) pigs. - Source: PubMed
Publication date: 2023/11/03
Broadwin MarkAghagoli GhazalSabe Sharif AHarris Dwight DWallace JoselynnLawson JordanRagayendran AshokFedulov Alexey VSellke Frank W - Congenital scoliosis (CS) is a congenital deformity of the spine resulting from abnormal and asymmetrical development of vertebral bodies during pregnancy. However, the etiology and mechanism of CS remain unclear. Epigenetics is the study of heritable variations in gene expression outside of changes in nucleotide sequence. Among these, DNA methylation was described first and is the most characteristic and most stable epigenetic mechanism. Therefore, in this study, we aim to explore the association between genome methylation and CS which are not been studied before. - Source: PubMed
Publication date: 2022/08/20
Wu YuanTaoZhang Hong-QiTang MingxingGuo ChaofengLiu ShaohuaLi JiongWang YunjiaXiao LigeYang Guanteng