Nancy S. Wexler

Bio: Nancy S. Wexler is an academic researcher from Hereditary Disease Foundation. The author has contributed to research in topics: Huntington's disease & Genetic linkage. The author has an hindex of 37, co-authored 63 publications receiving 22597 citations. Previous affiliations of Nancy S. Wexler include Columbia University.

A polymorphic DNA marker genetically linked to Huntington's disease

Abstract: Family studies show that the Huntington's disease gene is linked to a polymorphic DNA marker that maps to human chromosome 4. The chromosomal localization of the Huntington's disease gene is the first step in using recombinant DNA technology to identify the primary genetic defect in this disorder.

Unified huntington’s disease rating scale: Reliability and consistency

Abstract: The Unified Huntington's disease Rating Scale (UHDRS) was developed as a clinical rating scale to assess four domains of clinical performance and capacity in HD: motor function, cognitive function, behavioral abnormalities, and functional capacity. We assessed the internal consistency and the intercorrelations for the four domains and examined changes in ratings over time. We also performed an interrater reliability study of the motor assessment. We found there was a high degree of internal consistency within each of the domains of the UHDRS and that there were significant intercorrelations between the domains of the UHDRS, with the exception of the total behavioral score. There was an excellent degree of interrater reliability for the motor scores. Our limited longitudinal database indicates that the UHDRS may be useful for tracking changes in the clinical features of HD over time. The UHDRS assesses relevant clinical features of HD and appears to be appropriate for repeated administration during clinical studies.

Regional and cellular gene expression changes in human Huntington's disease brain.

Abstract: Huntington's disease (HD) pathology is well understood at a histological level but a comprehensive molecular analysis of the effect of the disease in the human brain has not previously been available. To elucidate the molecular phenotype of HD on a genome-wide scale, we compared mRNA profiles from 44 human HD brains with those from 36 unaffected controls using microarray analysis. Four brain regions were analyzed: caudate nucleus, cerebellum, prefrontal association cortex [Brodmann's area 9 (BA9)] and motor cortex [Brodmann's area 4 (BA4)]. The greatest number and magnitude of differentially expressed mRNAs were detected in the caudate nucleus, followed by motor cortex, then cerebellum. Thus, the molecular phenotype of HD generally parallels established neuropathology. Surprisingly, no mRNA changes were detected in prefrontal association cortex, thereby revealing subtleties of pathology not previously disclosed by histological methods. To establish that the observed changes were not simply the result of cell loss, we examined mRNA levels in laser-capture microdissected neurons from Grade 1 HD caudate compared to control. These analyses confirmed changes in expression seen in tissue homogenates; we thus conclude that mRNA changes are not attributable to cell loss alone. These data from bona fide HD brains comprise an important reference for hypotheses related to HD and other neurodegenerative diseases.

Tandem repeats finder: a program to analyze DNA sequences

Abstract: A tandem repeat in DNA is two or more contiguous, approximate copies of a pattern of nucleotides. Tandem repeats have been shown to cause human disease, may play a variety of regulatory and evolutionary roles and are important laboratory and analytic tools. Extensive knowledge about pattern size, copy number, mutational history, etc. for tandem repeats has been limited by the inability to easily detect them in genomic sequence data. In this paper, we present a new algorithm for finding tandem repeats which works without the need to specify either the pattern or pattern size. We model tandem repeats by percent identity and frequency of indels between adjacent pattern copies and use statistically based recognition criteria. We demonstrate the algorithm’s speed and its ability to detect tandem repeats that have undergone extensive mutational change by analyzing four sequences: the human frataxin gene, the human β T cell receptor locus sequence and two yeast chromosomes. These sequences range in size from 3 kb up to 700 kb. A World Wide Web server interface at c3.biomath.mssm.edu/trf.html has been established for automated use of the program.