Norma P. Tavakoli

Norma P. Tavakoli

Clinical Assistant Professor
School of Public Health
Department of Biomedical Sciences
Education

PhD Bristol University, Bristol, England (1994)
Postdoctoral training: New York State Department of Health, Wadsworth Center

A portrait of Norma P. Tavakoli.
About

The Newborn Screening Program at Wadsworth Center tests for over 40 genetic disorders in newborns. Infants who have one of several rare genetic disorders and infants who have been exposed to HIV are identified promptly; with medical treatment serious disease can often be prevented. One of the tests is molecular detection of cystic fibrosis (CF) by screening for a mutation panel in the CFTR gene. Certain mutations in this gene cause severe phenotype and are well-defined. The gold standard for a CF diagnosis is a sweat chloride test.

Screening has uncovered individuals whose sweat chloride values are above normal, but no other CF symptoms are identified. Our aim is to determine if other variants in the CFTR gene correlate with these abnormal sweat chloride levels. This will be carried out by searching for other variants in the CFTR gene and also modifier genes (other genes that may modulate sweat chloride values). Mutations in the CFTR gene will be detected by obtaining sequence information of the entire coding region for four groups: patients with abnormal sweat chloride values, patients with no disease but elevated immunoreactive trypsinogen (IRT), newborn CF mutation carriers with no disease and newborns with negative screens. Additionally, sequence information will be obtained for modifier genes, including TGFB1, which has been associated with CF severity.

A different newborn screening test that is provided detects Krabbe disease, which is caused by the deficient activity of galactosylceramidase (GALC gene). Expression studies to determine the enzyme activity resulting from mutations in the GALC gene compared to activities present when the normal gene is expressed will be performed in order to better understand and perhaps predict the clinical presentation, evolution and prognosis of the disease.