Scrolling Headlines:

Former Canisius guard Zach Lewis to transfer to UMass -

Tuesday, May 19, 2015

Letter: Deflate-Gate, where’s the air? -

Monday, May 18, 2015

Derrick Gordon announces he will transfer to Seton Hall -

Sunday, May 17, 2015

UMass baseball closes season out with series victory over George Mason -

Sunday, May 17, 2015

UMass to allow four student businesses to accept Dining Dollars next year -

Saturday, May 16, 2015

UMass baseball stymied by John Williams in loss to George Mason -

Friday, May 15, 2015

Jury sentences Tsarnaev to death -

Friday, May 15, 2015

Stop ignoring your white privilege -

Thursday, May 14, 2015

UMass basketball scheduled for showdown with Ole Miss in 2015 Holiday Showcase game -

Wednesday, May 13, 2015

Letter: Wall is a regression towards racial inequality -

Wednesday, May 13, 2015

UMass falls to Fairfield in extra innings in final home game -

Tuesday, May 12, 2015

UMass basketball recruit Marcquise Reed chooses Clemson -

Monday, May 11, 2015

UMass baseball drops Senior Day rubber match against URI -

Monday, May 11, 2015

Letter: Shocked at radio host’s ban from WMUA -

Monday, May 11, 2015

UMass women’s lacrosse falls in second round of NCAA tournament against top-seeded Maryland -

Sunday, May 10, 2015

Neil deGrasse Tyson: ‘It’s okay not to know’ -

Friday, May 8, 2015

Defense, Eipp’s five goals lead UMass women’s lacrosse past Jacksonville in NCAA tournament -

Friday, May 8, 2015

Quianna Diaz-Patterson closes book on historic senior season, successful career for UMass softball -

Friday, May 8, 2015

UMass men’s lacrosse overcomes early struggles to make 2015 playoff run -

Thursday, May 7, 2015

UMass softball fails to reach expectations in up-and-down 2015 season -

Wednesday, May 6, 2015

Advertisement

UMass study reveals genetic links with disease

Chris Roy/Collegian

A new approach to data analysis has led University of Massachusetts biostatisticians to discover new genetic information linked to common diseases such as diabetes and heart disease, according to a UMass press release.

The team of researchers, led by Andrea Foulkes, has applied this new approach to data analysis to pre-existing databases, revealing the genetic information behind that which causes conditions such as high cholesterol and heart diseases, according to the release.

Foulkes directs the Institute for Computational Biology, Biostatistics and Bioinformatics at UMass. Other members of her team include Rongheng Lin, an assistant professor, and Gregory Matthews and Ujjwall Das, who are both postdoctoral researchers. The work done by the team was supported by the National Institutes of Health National Heart, Lung and Blood Institute, the release stated.

“This new approach to data analysis provides opportunities for developing new treatments. It also advances approaches to identifying people at greatest risk for heart disease,” said Foulkes in the release.

The new style of analysis coined “MixMAP,” which was developed by Foulkes and cardiologist Dr. Muredach Reilly at the University of Pennsylvania, stands for “Mixed modeling of Meta-Analysis P-values,” according to the release. Since this method of statistical analysis is based on pre-existing public information, it “represents a low-cost tool” for researchers, according to the release.

“Another important point is that our method is straightforward to use with freely available computer software and can be applied broadly to advance genetic knowledge of many diseases,” Foulkes added in the release.

Foulkes explained that the new method takes the entire human genome into account and can be generalized to figure out many different diseases. Though the other more widely-used methods of gene tracking and analysis look for a “needle in a haystack,” so to speak, as a disease signal, according to the release, Foulkes’ new method makes use of genome knowledge in DNA regions that “contain several genetic signals for disease variation clumped together. … Thus, it is able to detect groups of unusual variants.”

According to the release, Foulkes characterizes the “MixMAP” technique as a discovery method still in need of scientific validation, although it “goes farther than usual by using sophisticated modeling approaches to quantify error.”

“We’ve done better than simply identify the strongest signals, we’ve quantified measures of association to show they are statistically meaningful,” noted Foulkes in the release.

George Felder can be reached at gfelder@student.umass.edu

Leave A Comment

You must be logged in to post a comment.