Automated Author ProfileZhang, Dongxi
Zhang, Dongxi
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: 2.6 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Recent studies suggest immunophenotypes may play a role in asthma, but their causal relationship has not been thoroughly examined. We used single nucleotide polymorphism (SNP)-derived instrumental variables. Summary data from 731 immune cell profiles and asthma cases were analyzed from genome-wide association studies (GWAS) of European populations. Mendelian Randomization (MR) analyses included inverse variance weighted (IVW), weighted median, and MR–Egger methods. Pleiotropy was assessed using the MR-Egger intercept and MR pleiotropy residual sum and outlier (MR-PRESSO) tests. Reverse MR analysis explored bidirectional causation between asthma and immunophenotypes. All statistical analyses were conducted using R software. MR analysis identified 108 immune signatures potentially contributing to asthma. Two immunophenotypes were significantly associated with asthma risk: CD4+ secreting Treg cells in allergic asthma (ORIVW =1.078; 95% CI: 1.036–1.122; PIVW =0.0002) and IgD + CD38- %lymphocyte cells in non-allergic asthma (ORIVW =1.123; 95% CI: 1.057–1.194; PIVW =0.0002). This study highlights the causal associations between specific immunophenotypes and asthma risk, providing new insights into asthma pathogenesis.
Authors
- Xu, Shengshan ;
- Liang, Jiahua ;
- Shen, Tao ;
- Zhang, Dongxi ;
- Lu, Zhuming
Recent studies suggest immunophenotypes may play a role in asthma, but their causal relationship has not been thoroughly examined. We used single nucleotide polymorphism (SNP)-derived instrumental variables. Summary data from 731 immune cell profiles and asthma cases were analyzed from genome-wide association studies (GWAS) of European populations. Mendelian Randomization (MR) analyses included inverse variance weighted (IVW), weighted median, and MR–Egger methods. Pleiotropy was assessed using the MR-Egger intercept and MR pleiotropy residual sum and outlier (MR-PRESSO) tests. Reverse MR analysis explored bidirectional causation between asthma and immunophenotypes. All statistical analyses were conducted using R software. MR analysis identified 108 immune signatures potentially contributing to asthma. Two immunophenotypes were significantly associated with asthma risk: CD4+ secreting Treg cells in allergic asthma (ORIVW = 1.078; 95% CI: 1.036–1.122; PIVW = 0.0002) and IgD + CD38− %lymphocyte cells in non-allergic asthma (ORIVW = 1.123; 95% CI: 1.057–1.194; PIVW = 0.0002). This study highlights the causal associations between specific immunophenotypes and asthma risk, providing new insights into asthma pathogenesis.
Authors
- Xu, Shengshan ;
- Liang, Jiahua ;
- Shen, Tao ;
- Zhang, Dongxi ;
- Lu, Zhuming
Recent studies suggest immunophenotypes may play a role in asthma, but their causal relationship has not been thoroughly examined. We used single nucleotide polymorphism (SNP)-derived instrumental variables. Summary data from 731 immune cell profiles and asthma cases were analyzed from genome-wide association studies (GWAS) of European populations. Mendelian Randomization (MR) analyses included inverse variance weighted (IVW), weighted median, and MR–Egger methods. Pleiotropy was assessed using the MR-Egger intercept and MR pleiotropy residual sum and outlier (MR-PRESSO) tests. Reverse MR analysis explored bidirectional causation between asthma and immunophenotypes. All statistical analyses were conducted using R software. MR analysis identified 108 immune signatures potentially contributing to asthma. Two immunophenotypes were significantly associated with asthma risk: CD4+ secreting Treg cells in allergic asthma (ORIVW = 1.078; 95% CI: 1.036–1.122; PIVW = 0.0002) and IgD + CD38− %lymphocyte cells in non-allergic asthma (ORIVW = 1.123; 95% CI: 1.057–1.194; PIVW = 0.0002). This study highlights the causal associations between specific immunophenotypes and asthma risk, providing new insights into asthma pathogenesis.
Authors
- Xu, Shengshan ;
- Liang, Jiahua ;
- Shen, Tao ;
- Zhang, Dongxi ;
- Lu, Zhuming