Disease development is often shaped by genetics, with how much or how little a gene is expressed influencing disease risk. While advances in technology and sequencing methods has led to a greater understanding of gene structure, location and function, conventional genetic studies often fail to connect genetic variants to actual changes in gene expression, particularly in rare or unique brain cell types. A new tool aims to change that.
A team led by researchers from Penn State College of Medicine has developed a new method that substantially improves the ability to map the genetic variants that drive disease, particularly neurodegenerative diseases. Instead of analyzing genetic effects by grouping cells into specific categories and determining genetic effects for each type individually, the team modeled the effects shared among seven different brain cell types.
The new approach, published in Nature Communications, outperforms existing methodologies, identifying approximately 75% more genes of interest. The researchers also found new genes linked to the risk of Alzheimer's disease and amyotrophic lateral sclerosis (ALS) and therapeutic targets, some of which have already-existing promising treatments.
"There's a lot of emphasis on data generation, but relatively modest efforts devoted to better analyzing the data. There's a lot more information that could be extracted from existing data sets and our work seeks to better digest this information," said Bibo Jiang, assistant professor of public health sciences at Penn State College of Medicine and senior author of the study. "It has the potential to create a new paradigm for understanding brain related disease."
