Automated Author ProfileSouza, Carolina F.M De
Souza, Carolina F.M De
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: 1.5 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Abstract Lysosomal storage disorders (LSDs) constitute a heterogeneous group of approximately 50 genetic disorders. LSDs diagnosis is challenging due to variability in phenotype penetrance, similar clinical manifestations, and a high allelic heterogeneity. A powerful tool for the diagnosis of the disease could reduce the “diagnostic odyssey” for affected families, leading to an appropriate genetic counseling and a better outcome for current therapies, since enzyme replacement therapies have been approved in Brazil for Gaucher, Fabry, and Pompe diseases, and are under development for Niemann-Pick Type B. However, application of next-generation sequencing (NGS) technology in the clinical diagnostic setting requires a previous validation phase. Here, we assessed the application of this technology as a fast, accurate, and cost-effective method to determine genetic diagnosis in selected LSDs. We have designed two panels for testing simultaneously 11 genes known to harbor casual mutations of LSDs. A cohort of 58 patients was used to validate those two panels, and the clinical utility of these gene panels was tested in four novel cases. We report the assessment of a NGS approach as a new tool in the diagnosis of LSDs in our service.
Authors
- Málaga, Diana Rojas ;
- Brusius-Facchin, Ana Carolina ;
- Siebert, Marina ;
- Pasqualim, Gabriela ;
- Saraiva-Pereira, Maria Luiza ;
- Souza, Carolina F.M De ;
- Schwartz, Ida V.D. ;
- Matte, Ursula ;
- Giugliani, Roberto
Abstract Lysosomal storage disorders (LSDs) constitute a heterogeneous group of approximately 50 genetic disorders. LSDs diagnosis is challenging due to variability in phenotype penetrance, similar clinical manifestations, and a high allelic heterogeneity. A powerful tool for the diagnosis of the disease could reduce the “diagnostic odyssey” for affected families, leading to an appropriate genetic counseling and a better outcome for current therapies, since enzyme replacement therapies have been approved in Brazil for Gaucher, Fabry, and Pompe diseases, and are under development for Niemann-Pick Type B. However, application of next-generation sequencing (NGS) technology in the clinical diagnostic setting requires a previous validation phase. Here, we assessed the application of this technology as a fast, accurate, and cost-effective method to determine genetic diagnosis in selected LSDs. We have designed two panels for testing simultaneously 11 genes known to harbor casual mutations of LSDs. A cohort of 58 patients was used to validate those two panels, and the clinical utility of these gene panels was tested in four novel cases. We report the assessment of a NGS approach as a new tool in the diagnosis of LSDs in our service.
Authors
- Málaga, Diana Rojas ;
- Brusius-Facchin, Ana Carolina ;
- Siebert, Marina ;
- Pasqualim, Gabriela ;
- Saraiva-Pereira, Maria Luiza ;
- Souza, Carolina F.M De ;
- Schwartz, Ida V.D. ;
- Matte, Ursula ;
- Giugliani, Roberto