Automated Author ProfileWang, Rongsheng
Wang, Rongsheng
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
To validate the potential of the serotonin receptor encoded by 5-hydroxytryptamine receptor 2A (HTR2A) cg15692052 DNA methylation as a diagnostic biomarker for rheumatoid arthritis (RA) and its subtypes. MethylTargetTM targeted region methylation sequencing technology was employed to analyze the DNA methylation levels of HTR2A cg15692052 in RA, health control, ankylosing spondylitis, psoriatic arthritis, gout, systemic lupus erythematosus, dermatomyositis, and primary Sjögren’s syndrome patients within the region of chr13:46898190~chr13:46897976. Machine learning algorithms were used to analyze data. Compared to the HC group, RA patients and four serological subtypes of RA (RF-negative RA, RF/CCP double-positive, RF/CCP double-negative, and CCP-negative RA) exhibited significantly higher levels of HTR2A cg15692052 methylation (p < 0.05). Methylation levels in RA patients and its four serological subtypes were significantly positively correlated with erythrocyte sedimentation rate or C-reactive protein (p < 0.05). HTR2A cg15692052 methylation levels combined with different clinical features can significantly distinguish RA patients with AUCs ranging from 0.672 to 0.757, RF/CCP double-negative patients with AUCs from 0.825 to 0.966, RF/CCP double-positive RA patients with AUCs from 0.714 to 0.846, and RF-negative RA patients with AUCs from 0.928 to 0.932. The HTR2A cg15692052 DNA methylation level can serve as a diagnostic biomarker for RA and its subtypes. Rheumatoid arthritis is a long-term condition that causes pain, swelling, and stiffness in the joints. Getting an early and accurate diagnosis is very important, but some patients do not show typical signs in regular blood tests, making it hard to detect the disease in time. In this study, we looked at whether a specific chemical change in the body – namely, DNA methylation, which can affect how genes work – could help identify people with rheumatoid arthritis more reliably. We focused on one gene in particular, called HTR2A, and compared this chemical change in people with rheumatoid arthritis, healthy individuals, and people with other joint problems. We found that this signal was noticeably different in people with rheumatoid arthritis, even in those who usually go undetected by common tests. These results suggest that checking for such gene-related changes could help doctors find and treat rheumatoid arthritis earlier, especially in patients who might otherwise be missed.
Authors
- Zhao, Jianan ;
- He, Binghen ;
- Li, Yunshen ;
- Shan, Yu ;
- Wei, Kai ;
- Jiang, Ping ;
- Shi, Yiming ;
- Zheng, Yixin ;
- Zhao, Fuyu ;
- Yang, Guizhen ;
- Li, Qianqian ;
- Zhou, Mi ;
- Guo, Shicheng ;
- Zheng, Yuejuan ;
- Jiao, Juan ;
- Wang, Rongsheng ;
- Chang, Cen ;
- Lv, Liangjing
To validate the potential of the serotonin receptor encoded by 5-hydroxytryptamine receptor 2A (HTR2A) cg15692052 DNA methylation as a diagnostic biomarker for rheumatoid arthritis (RA) and its subtypes. MethylTargetTM targeted region methylation sequencing technology was employed to analyze the DNA methylation levels of HTR2A cg15692052 in RA, health control, ankylosing spondylitis, psoriatic arthritis, gout, systemic lupus erythematosus, dermatomyositis, and primary Sjögren’s syndrome patients within the region of chr13:46898190~chr13:46897976. Machine learning algorithms were used to analyze data. Compared to the HC group, RA patients and four serological subtypes of RA (RF-negative RA, RF/CCP double-positive, RF/CCP double-negative, and CCP-negative RA) exhibited significantly higher levels of HTR2A cg15692052 methylation (p < 0.05). Methylation levels in RA patients and its four serological subtypes were significantly positively correlated with erythrocyte sedimentation rate or C-reactive protein (p < 0.05). HTR2A cg15692052 methylation levels combined with different clinical features can significantly distinguish RA patients with AUCs ranging from 0.672 to 0.757, RF/CCP double-negative patients with AUCs from 0.825 to 0.966, RF/CCP double-positive RA patients with AUCs from 0.714 to 0.846, and RF-negative RA patients with AUCs from 0.928 to 0.932. The HTR2A cg15692052 DNA methylation level can serve as a diagnostic biomarker for RA and its subtypes. Rheumatoid arthritis is a long-term condition that causes pain, swelling, and stiffness in the joints. Getting an early and accurate diagnosis is very important, but some patients do not show typical signs in regular blood tests, making it hard to detect the disease in time. In this study, we looked at whether a specific chemical change in the body – namely, DNA methylation, which can affect how genes work – could help identify people with rheumatoid arthritis more reliably. We focused on one gene in particular, called HTR2A, and compared this chemical change in people with rheumatoid arthritis, healthy individuals, and people with other joint problems. We found that this signal was noticeably different in people with rheumatoid arthritis, even in those who usually go undetected by common tests. These results suggest that checking for such gene-related changes could help doctors find and treat rheumatoid arthritis earlier, especially in patients who might otherwise be missed.
Authors
- Zhao, Jianan ;
- He, Binghen ;
- Li, Yunshen ;
- Shan, Yu ;
- Wei, Kai ;
- Jiang, Ping ;
- Shi, Yiming ;
- Zheng, Yixin ;
- Zhao, Fuyu ;
- Yang, Guizhen ;
- Li, Qianqian ;
- Zhou, Mi ;
- Guo, Shicheng ;
- Zheng, Yuejuan ;
- Jiao, Juan ;
- Wang, Rongsheng ;
- Chang, Cen ;
- Lv, Liangjing