GDF3

Last update 08 May 2025

Basic Info

Synonyms

GDF-3, GDF3, growth differentiation factor 3

+ [1]

Introduction

Growth factor involved in early embryonic development and adipose-tissue homeostasis. During embryogenesis controls formation of anterior visceral endoderm and mesoderm and the establishment of anterior-posterior identity through a receptor complex comprising the receptor ACVR1B and the coreceptor CRIPTO (By similarity). Regulates adipose-tissue homeostasis and energy balance under nutrient overload in part by signaling through the receptor complex based on ACVR1C and CRIPTO/Cripto (PubMed:21805089).

100 Clinical Results associated with GDF3

100 Translational Medicine associated with GDF3

0 Patents (Medical) associated with GDF3

195

Literatures (Medical) associated with GDF3

01 Jan 2025·Theriogenology

Analysis of the pluripotent and germline marker gene expression, and the state of X chromosome reactivation of primordial germ cells in pig gonads

Article

Author: Liu, Zhonghua ; Yan, Tingsheng ; Yang, Zhishan ; Yuan, Wenjing ; Weng, Xiaogang ; Zhou, Yang ; Ma, Xinghong ; Zhang, Yuting ; Zhang, Qi

The gonadal primordial germ cells (PGCs) possess a unique state of pluripotency and X chromosome activity. However, extensive evidence indicates developmental variability in PGCs across different species. This study aims to evaluate the pluripotency status, specific gene expression patterns, and X chromosome reactivation (XCR) of pig gonadal PGCs. Single-cell RNA-seq revealed significant heterogeneity within the population of gonadal PGCs. Notably, these PGCs expressed high levels of pluripotency markers OCT4, PRDM14, and NANOG, while lacking SOX2 expression. Through the screening of marker genes and subsequent protein expression validation, we identified growth differentiation factor 3 (GDF3) as a specific surface marker for pig gonadal PGCs, facilitating their efficient purification for further study. Furthermore, analysis of gonadal PGCs demonstrated complete XCR. This was evidenced by the absence of repressive histone modifications (H3K27me3, H3K9me3, and H2AK119ub), the lack of X inactive specific transcript (XIST) RNA FISH signal, and the doubled expression of X-linked genes. Additionally, these PGCs expressed high levels of genes associated with epigenetic modification, chromatin remodeling, and XIST-associated RNA-binding. These factors likely play a crucial role in regulating pluripotency and X chromosome activity. In summary, this study reveals the heterogeneity in pig gonadal PGCs and identifies GDF3 as a specific surface marker. It also elucidates the expression patterns of pluripotency transcription factors and the events involved in XCR.

01 Jan 2025·Phytomedicine

Total saponins from Panax japonicus mediate the paracrine interaction between adipocytes and macrophages to promote lipolysis in the adipose tissue during aging via the NLRP3 inflammasome/GDF3/ATGL axis

Article

Author: Zhu, Leiqi ; Hu, Yaqi ; Xia, Fangqi ; Xue, Mengzhen ; He, Yumin ; Yuan, Chengfu ; Wang, Yaqi ; Yuan, Qi ; Zhang, Yifan ; Wang, Shuwen ; Zhang, Jihong ; Li, Yuanyang ; Wang, Rui ; Yuan, Ding

Adipocytic lipolysis is strongly related to the increase of visceral fat, decrease of exercise capacity, and various other metabolic syndromes during aging. It is significantly influenced by the paracrine relationship between adipocytes and the adipose tissue macrophages (ATMs), and the cytokines secreted by ATMs have endocrine effects on adjacent tissues. We previously reported that the total saponins from Panax japonicus (TSPJs) can enhance lipid metabolism. In this work, we for the first time proved that TSPJs promoted adipocytic lipolysis by preventing NLRP3 activation in ATMs to inhibit the expression of GDF3. The decrease of GDF3 by TSPJs restored the expression of the adipose triglyceride lipase (ATGL) and phosphorylated hormone-sensitive lipase (p-HSL), both of which are known to decrease with aging. Thus, the NLRP3 inflammasome/GDF3/ATGL axis may be a worthy target in developing future clinical solutions for aging-related obesity.

01 Dec 2024·Archives of Toxicology

Predictive biomarkers for embryotoxicity: a machine learning approach to mitigating multicollinearity in RNA-Seq

Article

Author: Lee, Seung-Jin ; Jeong, Ji-Seong ; Jung, Soontag ; Ham, Onju ; Kim, Sangyun ; Park, Seung-Chun ; Yu, Wook-Joon ; Chan, Jireh Yi-Le ; Quah, Yixian ; Kim, Woojin

Multicollinearity, characterized by significant co-expression patterns among genes, often occurs in high-throughput expression data, potentially impacting the predictive model's reliability. This study examined multicollinearity among closely related genes, particularly in RNA-Seq data obtained from embryoid bodies (EB) exposed to 5-fluorouracil perturbation to identify genes associated with embryotoxicity. Six genes-Dppa5a, Gdf3, Zfp42, Meis1, Hoxa2, and Hoxb1-emerged as candidates based on domain knowledge and were validated using qPCR in EBs perturbed by 39 test substances. We conducted correlation studies and utilized the variance inflation factor (VIF) to examine the existence of multicollinearity among the genes. Recursive feature elimination with cross-validation (RFECV) ranked Zfp42 and Hoxb1 as the top two among the seven features considered, identifying them as potential early embryotoxicity assessment biomarkers. As a result, a t test assessing the statistical significance of this two-feature prediction model yielded a p value of 0.0044, confirming the successful reduction of redundancies and multicollinearity through RFECV. Our study presents a systematic methodology for using machine learning techniques in transcriptomics data analysis, enhancing the discovery of potential reporter gene candidates for embryotoxicity screening research, and improving the predictive model's predictive accuracy and feasibility while reducing financial and time constraints.

Analysis

Perform a panoramic analysis of this field.

view full example data

AI Agents Built for Biopharma Breakthroughs

Accelerate discovery. Empower decisions. Transform outcomes.

Get started for free today!

Accelerate Strategic R&D decision making with Synapse, PatSnap’s AI-powered Connected Innovation Intelligence Platform Built for Life Sciences Professionals.

Start your data trial now!

Synapse data is also accessible to external entities via APIs or data packages. Empower better decisions with the latest in pharmaceutical intelligence.

Bio

Bio Sequences Search & Analysis

Chemical

Chemical Structures Search & Analysis

GDF3

Basic Info

Related

Analysis