Disease Severity Predicted by Computer Model

A study has shown that a computer model can be used to predict phenotypic behavior based on genetic information obtained from mapping of single nucleotide polymorphisms (SNPs). The study was published in the November 2002 issue of Genome Research.

Single nucleotide polymorphisms are DNA sequence variations that occur when a single nucleotide (A,T,C,or G) in the genome sequence is changed. About two-thirds of all SNPs involve the replacement of cytosine (C) with thymine (T). SNPs occur every 100 to 300 bases along the human genome and are stable from an evolutionarily standpoint, making them easier to follow in population studies.

In the current study, researchers from the University of California, San Diego (UCSD, USA; www.ucsd.edu) used a computer model to relate specific genetic mutations to exact variations of a disease. They reviewed genetic information from patients who had an enzyme deficiency that caused hemolytic anemia. By inserting specific DNA sequences into a computer model for red blood cell metabolism, it was possible to predict accurately which mutations would result in chronic hemolytic anemia and which would cause a less severe version of the disease.

"The model is like the wiring diagram or design drawings for the cell,” explained senior author Dr. Bernhard Palsson, of the bioengineering department at UCSD. "It incorporates all the genes in the cell, the products of each, and the interwoven process of how those products interact to produce cellular functions. Once we have this computer model, it is in principle a fairly straightforward process to alter a specific DNA sequence, run a simulation on the program, and receive information back about how the defect impacts the cell's function.”

"Eventually, there could be a kind of databank of specific genetic mutations that cause precise disease variants,” said Dr. Palsson. "Some mutations will be severe, others benign. And every variation of a disease could be treated differently. This could be incredibly useful for drug development and will aid physicians in creating effective treatment plans for individuals.”



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