New Statistical Tool May Help Detect Novel Genes Linked to Heart Disease, Penn Study Reports

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Media Contact:Jessica Mikulski | jessica.mikulski@uphs.upenn.edu | 215-349-8369February 8, 2013

PHILADELPHIA — Researchers at the Perelman School of Medicine at the University of Pennsylvania and the University of Massachusetts Amherst report in the latest edition of PLOS ONE utilizing a novel statistical tool to analyze existing large databases of genetic information to mine new information about genes that modulate low density lipoprotein (LDL) cholesterol and its downstream consequences, heart attack, stroke and death.  This new approach to analyzing existing data suggested a dozen new LDL cholesterol genes for analysis and provides opportunities for developing new treatments and advancing approaches to identifying those at greatest risk for heart disease.

he new analytical approach, called “mixed modeling of meta-analysis P-values” or MixMAP, offers new and complementary information as compared to single nucleotide polymorphism-based analysis approaches that have been used in past studies to identify novel genes linked to heart disease. The researchers say the tool is straightforward to implement and can be used with freely available computer software.  The approach may also be applied broadly to advance genetic knowledge of many other diseases.

“The MixMAP approach provides a significant advance by unlocking more information regarding the genetic basis of disease using existing large data and at little additional cost to the research community and funding agencies,” said Muredach P. Reilly, MBBCH, MSC, associate professor of Medicine at Penn and senior study author.  “For complex diseases such as heart attack and diabetes, this provides a real opportunity to generate substantial new knowledge and advance treatment and diagnostic opportunities."

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