Automated Author ProfileYu, TW
Yu, TW
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: 1.4 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Although autism has a clear genetic component, the high genetic heterogeneity of the disorder has been a challenge for the identification of causative genes. We used homozygosity analysis to identify probands from nonconsanguineous families that showed evidence of distant shared ancestry, suggesting potentially recessive mutations. Whole-exome sequencing of 16 probands revealed validated homozygous, potentially pathogenic recessive mutations that segregated perfectly with disease in 4/16 families. The candidate genes (UBE3B, CLTCL1, NCKAP5L, ZNF18) encode proteins involved in proteolysis, GTPase-mediated signaling, cytoskeletal organization, and other pathways. Furthermore, neuronal depolarization regulated the transcription of these genes, suggesting potential activity-dependent roles in neurons. We present a multidimensional strategy for filtering whole-exome sequence data to find candidate recessive mutations in autism, which may have broader applicability to other complex, heterogeneous disorders
Authors
- Gabriel, SB ;
- Greenberg, ME ;
- ARRA Autism Sequencing Collaboration ;
- Schubert, CR ;
- Stevens, CR ;
- Hill, RS ;
- Coulter, ME ;
- Ataman, B ;
- Lim, ET ;
- Yu, TW ;
- Chahrour, MH ;
- Walsh, CA
NOTE: DO NOT SHARE. Despite significant heritability of autism spectrum disorders (ASDs), their extreme genetic heterogeneity has proven challenging for gene discovery. Studies of primarily simplex families have implicated de novo copy number changes and point mutations, but are not optimally designed to identify inherited risk alleles. We apply whole-exome sequencing (WES) to ASD families enriched for inherited causes due to consanguinity and find familial ASD associated with biallelic mutations in disease genes (AMT, PEX7, SYNE1, VPS13B, PAH, and POMGNT1). At least some of these genes show biallelic mutations in nonconsanguineous families as well. These mutations are often only partially disabling or present atypically, with patients lacking diagnostic features of the Mendelian disorders with which these genes are classically associated. Our study shows the utility of WES for identifying specific genetic conditions not clinically suspected and the importance of partial loss of gene function in ASDs.
Authors
- Et Al. ;
- Mukaddes, NM ;
- Al-Saffar, M ;
- Kwan, BY ;
- Hill, RS ;
- Joseph, RM ;
- Ware, J ;
- Nasir, RH ;
- Rodriguez, J ;
- Felie, JM ;
- Sunu, CM ;
- Partlow, JN ;
- Mochida, GH ;
- Sanders, SJ ;
- Lim, ET ;
- D'Gama, AM ;
- Malik, AN ;
- Adli, M ;
- Harmin, DA ;
- Schmitz-Abe, K ;
- Ataman, B ;
- Okamura-Ikeda, K ;
- Jiralerspong, S ;
- Coulter, ME ;
- Chahrour, MH ;
- Yu, TW ;
- Walsh, CA