Stanford researchers join national effort to learn how genetic variation affects health

Five Stanford researchers will participate in a $180 million nationwide campaign by the National Institutes of Health to understand the effect of human-genome variations on health and disease.

- By Krista Conger

Clockwise from top left, Ansuman Satpathy, Jesse Engreitz, Thomas Quertermous, Anshul Kundaje and Mike Cherry are part of a consortium that is identifying and mapping the human genome to better understand disease.

Five Stanford Medicine faculty members have received more than $40 million from the National Institutes of Health as part of a $180 million, five-year endeavor to understand how variations in the human genome — those affecting DNA sequence, three-dimensional structure and the pattern of chemical tags that regulate the expression of genes along its length — influence human health and disease.

The research is expected to help clinicians better predict an individual’s disease risk and to provide clues about the molecular causes of poorly understood diseases.

The new consortium, the Impact of Genomic Variation on Function, brings together researchers from 30 institutions to identify, map and catalog regions in the human genome critical to its function. The consortium’s goal is an extension of the decadeslong push to learn how a person’s genetic code, coupled with environment and lifestyle, affects that person’s likelihood of developing a wide variety of conditions.  

The researchers are professor of genetics Mike Cherry, PhD; assistant professor of genetics Jesse Engreitz, PhD; assistant professor of genetics and of computer science Anshul Kundaje, PhD; assistant professor of pathology Ansuman Satpathy, MD, PhD; and professor of cardiovascular medicine Thomas Quertermous, MD.

Since the first sequencing of the human genome in the early 2000s, researchers have identified tens of thousands of disease-associated variations, usually by comparing the complete DNA sequences of many people and pinpointing specific changes that occur more commonly in individuals with a particular disease or health condition.

Some of the variations that have been identified change the structure — and thus the physiological function — of the protein encoded by a gene in the DNA sequence. Others occur in regulatory regions that control how and when certain genes are expressed. Still others change the three-dimensional structure of the genome or the prevalence of chemical tags on the DNA that control gene function.

In some cases, these changes can be directly linked via molecular pathways to the development of a disease being studied. Sickle cell anemia, for example, is caused by a single mutation in the gene that encodes a protein in red blood cells called beta hemoglobin. The mutated beta hemoglobin molecules fold incorrectly, forcing the red blood cell into a sickle shape that delivers oxygen inefficiently and causes patients pain, fatigue and other symptoms.

A close look at variants

But more than 90% of variants occur in noncoding regions of the genome, and it remains unclear whether or how many of them are connected to specific disease processes. Members of the consortium will use laboratory methods and computer modeling to uncover the functions of these variants.

Satpathy was awarded $13 million to launch the Single-Cell Mapping Center for Human Regulatory Elements and Gene Activity. Researchers at the center will generate an open-source map detailing genetic regulatory elements, the three-dimensional structure of chromatin, and the gene and protein expression profiles of single cells in a variety of organ systems and tissue types, in both healthy people and those with various immune-related diseases.

Engreitz and Quertermous were awarded nearly $8.5 million to jointly head the Stanford Center for Connecting DNA Variants to Function and Phenotype. Their goal is to interpret how noncoding regions of the human genome are associated with the development of specific cardiac diseases in adults and children. They will use genetic mapping, genetic engineering and computer methods to understand the connection between genomic variation in cardiovascular cells’ regulatory elements and their structure and function. These new connections will be used to catalog the effect of variants in many human cell types and diseases.

“It is a great pleasure to be part of this network of highly accomplished scientists in a joint effort to decipher the regulatory framework of the human genome,” Quertermous said. “The consortium’s insights will significantly accelerate efforts to understand how single nucleotide changes affect human traits and complex diseases.” 

Similarly, Kundaje was awarded nearly $4 million to predict the effects of genetic variation based on its context and location within regulatory regions. “Ultimately, our machine-learning models will generate a high-resolution functional sequence map of the human genome that will identify, for any cell type, cell state or location in the body, which noncoding variants affect the regulation of which nearby genes, and what those effects are,” Kundaje said. “Such a map will allow us to leverage the recent explosion of genome sequencing and molecular profiling techniques to understand the genetic basis of disease.”

More than $18 million was awarded to Cherry and Mark Gerstein, PhD, a professor of biomedical informatics, of molecular biophysics, of biochemistry and of computer science at Yale University, to co-lead a data administrative and coordinating center. They will evaluate and coordinate the use of the data and new software generated by the consortium and will maintain a database of the results for use by the biomedical research community.

“The guiding principles of this consortium are open science, open data and open-source software,” Cherry said. “This is a critical component of the consortium, bringing researchers from across the country together to generate complex data types via novel experimental assays, many of which focus on the single-cell level of gene expression. The center will help make this complex and high-quality data interoperable, findable and accessible.”

About Stanford Medicine

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2023 ISSUE 3

Exploring ways AI is applied to health care