Washington, Apr 2: Scientists at the Michigan Technological University
have successfully identified 11 gene variations linked to type 2
diabetes, with the help of a new mathematical model.

The researchers have developed powerful new tools for winnowing out the
genes behind some of humanity’s most intractable diseases, including
type 2 diabetes.

One of the tools, called Ensemble Learning Approach (ELA), enabled the
researchers to isolate 11 variations within genes, called single
nucleotide polymorphisms, SNPs or "snips," associated with type 2
diabetes.

Developed by Qiuying Sha, an assistant professor of mathematical
sciences, ELA is software that can detect a set of SNPs that jointly
have a significant effect on a disease.

"With chronic, complex diseases like Parkinson's, diabetes and ALS [Lou
Gehrig's disease], multiple genes are involved. You need a powerful
test," said Sha.

In case of complex inherited conditions, like type 2 diabetes, it is
possible for single genes to precipitate the disease on their own,
while other genes cause disease when they act together. Earlier, it was
cumbersome to find these gene-gene combinations as the calculations
needed to tally suspect genes among the 500,000 or so in the human
genome, have been quite difficult.

However, ELA rules out this problem, firstly by reducing the field of
potentially dangerous genes, and secondly, by applying statistical
methods to find out which SNPs act on their own and which act in
combination.

"We thought it was pretty cool," said Sha.

In order to test their model on real data, the researchers examined
genes from over 1,000 people in the United Kingdom, half with type
2 diabetes and half without. They singled out 11 SNPs that, singly or
in pairs, are linked to the disease with a high degree of probability.

ELA is used to compare the genetic makeup of unrelated individuals to
sort out disease-related genes. The researchers also developed another
approach, which uses a two-stage association test that incorporates
founders' phenotypes, called TTFP that can examine the genomes of
family members going back generations.

"In the past, researchers have dealt with the nuclear family, parents
and children, but this could go back to grandparents,
great-grandparents . . . as far back as you want,” said Sha.

But she added: "We don’t have the data sets yet to work with. That’s the problem with having no medical school."

The researchers have published their findings in the European Journal of Human Genetics. (ANI)