Work

Models of granulocyte DNA structure are highly predictive of myelodysplastic syndrome

Year: 2004

Type: article

Abstract: We have used statistical models based on Fourier transform-infrared spectra to differentiate between the DNA structure of normal granulocytes and those obtained from patients with myelodysplastic syndrome (MDS). The substantial degree of discrimination achieved between the two DNA groups is attributed to differences in the nucleotide base and backbone structures. These structural differences allowed for the development of a discriminant analysis model that predicted, with high sensitivity and specificity, which DNA came from normal granulocytes vs. granulocytes from MDS patients. The findings are a promising basis for developing a blood test to diagnose and predict the occurrence of MDS, for which there is currently a paucity of molecular markers.

Source: Proceedings of the National Academy of Sciences

DOI: 10.1073/pnas.0400838101

Authors: Donald C. Malins, Katie M. Anderson, Nayak L. Polissar, Gary K. Ostrander, Edward T. Knobbe, Virginia M. Green, Naomi K. Gilman, Jerry L. Spivak

Institutions: Johns Hopkins University, Johns Hopkins Medicine, Sciperio (United States)

Language: English

Topic: Spectroscopy Techniques in Biomedical and Chemical Research

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2016847372

FWCI: 1.743

Cites: 40

Cited by: 13

Related to: 10