Update to the Tuberous Sclerosis Complex (TSC) Natural History Database Studies
Posted December 13, 2007
Steven P. Sparagana, M.D., Texas Scottish Rite Hospital for Children, Dallas, Texas and Vicky Whittemore, Ph.D., Tuberous Sclerosis Alliance, Silver Spring, Maryland

Dr. Steven Sparagana of Texas Scottish Rite Hospital for Children and the University of Texas Southwestern Medical Center at Dallas began development of the TSC Natural History Database using funds from a Fiscal Year 2004 (FY04) Natural History Development Award. The TS Alliance and a consortium of TSC clinics completed development of this database (see, and the TS Alliance is currently leading this project (see This comprehensive clinical database of TSC cases documents the natural history and variability of TSC over the lifespan of individuals with the disease. Patient information collected for the database includes demographics, enrollment in the database, initial TSC diagnosis, genotype, participation in investigational studies, mortality, family history, prenatal history, vital signs, TSC-related diagnoses, diagnostic tests, and treatments. Understanding the clinical aspects of TSC could lead to more accurate disease prognosis, development of new targeted therapies, and prediction of patient response to treatments.

Phase I of the project was completed at the first two clinics (Minnesota Epilepsy Group, P.A.®, and Texas Scottish Rite Hospital for Children) in April 2007. As of June 2007, these two clinics enrolled more than 80 individuals with TSC, 80% of whom were children. The database was optimized during Phase I; Phase II of the project was launched in 2007. In this phase, the following six clinics are being added: The Carol and James Herscot Center for Children and Adults with Tuberous Sclerosis Complex at Massachusetts General Hospital; the Tuberous Sclerosis Center at New York University Medical Center; Washington Metro Area Tuberous Sclerosis Research Clinic; Chicago Corner Children's Hospital Neurogenetic Clinic; The Jack and Julia Center for TSC at Children's Hospital and Research Center at Oakland; and the TSC Clinic at UCLA. Additional TSC clinics are expected to be added in 2008.

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New Software for Cell Image Analysis
Posted November 14, 2007
David Sabatini, M.D., Ph.D. and Anne Carpenter, Ph.D., Whitehead Institute for Biomedical Research, Cambridge, Massachusetts

Dr. David Sabatini and Dr. Anne Carpenter of the Whitehead Institute for Biomedical Research have developed new image analysis software for identifying and quantifying cell phenotypes using funds from a Fiscal Year 2004 Tuberous Sclerosis Complex (TSC) Research Program Concept Award. Dr. Sabatini's team created this software to overcome limitations found in existing software packages, such as price, availability of applications, challenges in using algorithms and macros, and flexibility. Their program, CellProfiler, is the first free, open-source system designed for flexible, high-throughput cell image analysis. CellProfiler can be used for assaying cell count, size, per-cell protein levels, cell/organelle shape, and subcellular localization of DNA or protein.

Dr. Sabatini's group is using CellProfiler as part of a high throughput screen to identify new drug targets for treating TSC. The team is using cultured Drosophila cells as living cell microarrays, and they are identifying all the genes in the genome whose RNAi-mediated reduction in expression (1) prevents growth and proliferation of TSC1- or TSC2-deficient cells without affecting normal cells, (2) induces apoptosis and cell death in TSC1- or TSC2-deficient cells without killing normal cells, or (3) reverts TSC1- or TSC2-deficient cells to a normal phenotype.

In addition to TSC research, CellProfiler can be utilized for diverse types of biological research, and it has been used by several researchers for a variety of applications, including analysis of yeast, Drosophila, worm, and mammalian cells. As CellProfiler is already being employed to count cells, identify tumors, and quantify wound healing (see for more information), it clearly has the potential to speed TSC research, as well as other types of cell-based biological research.


Lamprecht M, Sabatini DM, and Carpenter AE. 2007. CellProfilerTM: Free, versatile software for automated biological image analysis. BioTechniques 42(1):71-75.

Jones TR, Carpenter AE, Golland P, and Sabatini DM. 2006. Methods for high-content, high-throughput image-based cell screening. MIABB 2006 Workshop Proceedings.

Carpenter AE, Jones TR, Wheeler DB, Lamprecht M, Clarke C, Friman O, Guertin DA, Kang IH, Lindquist R, Chang JH, Moffat J, Golland P, and Sabatini DM. 2006. CellProfiler: Image analysis software for identifying and quantifying cell phenotypes. Genome Biology 7:R100.


Abstract: Identifying Novel Drug Targets for the Treatment of Tuberous Sclerosis Complex Using High Throughput Technologies

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