School of Medicine researchers get two NIH grants

The Genotype-Tissue Expression project will examine genes’ behavior in cells.

School of Medicine scientists won two of eight grants recently awarded by the National Institutes of Health as part of its multiyear Genotype-Tissue Expression project.

The project builds on a national database of tissues and genomes and aims to strengthen the understanding of genetic expression in different human organs. 

Michael Snyder, PhD, professor and chair of genetics, and Hua Tang, PhD, associate professor of genetics, received about $2.5 million to investigate the ways protein levels vary among nine different tissue types. They plan to trace variations in protein levels back to variations in the genome, potentially revealing the mechanisms of diseases. Their grant was funded in part by the National Heart, Lung and Blood Institute.

Jin Billy Li, PhD, assistant professor of genetics, and Stephen Montgomery, PhD, assistant professor of pathology and genetics, received approximately $1.2 million to examine the tissue-specific levels of expression between alleles — variant forms of a gene inherited from each parent. For example, some alleles are more active in certain tissues than other versions. The team is examining the different alleles for 400 genes in an attempt to decipher the allele pairs that cause disease.

In addition, they also plan to expand the NIH’s tissue database by adding tissues from about 100 individuals from Stanford.  “This [grant] gives us the ability to generate what we think will be data of international importance,” Montgomery said. “It’s a considerable opportunity.”

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu.

2023 ISSUE 3

Exploring ways AI is applied to health care