Syndicate content

Thousands of Genes Influence Most Complex Diseases, Stanford Researchers Report in Cell; “Compelling Paper” Presents “Plausible and Fascinating Model”

A core assumption in the study of complex-disease-causing genes has been that they are clustered in molecular pathways directly connected to the disease. But work by a group of researchers at the Stanford University School of Medicine suggests otherwise. The gene activity of cells is so broadly networked that virtually any gene can influence disease, the researchers found. As a result, most of the heritability of complex diseases is due not to a handful of core genes, but to tiny contributions from vast numbers of peripheral genes that function outside disease pathways. Any given trait, it seems, is not controlled by a small set of genes. Instead, nearly every gene in the genome influences everything about us. The effects may be tiny, but they add up. The work is described in a Perspective piece published in the June 15, 2017 issue of Cell. Jonathan Pritchard (photo), PhD, Professor of Genetics and of Biology, is the senior author. Graduate student Evan Boyle and postdoctoral scholar Yang Li, PhD, share lead authorship. The article is titled “An Expanded View of Complex Traits: From Polygenic to Omnigenic.” The researchers call their provocative new understanding of complex disease genes an "omnigenic model" to indicate that almost any gene can influence complex diseases and other complex traits. In any cell, there might be 50 to 100 core genes with direct effects on a given complex trait, as well as easily another 10,000 peripheral genes that are expressed in the same cell with indirect effects on that complex trait, said Dr. Pritchard, who is also a Howard Hughes Medical Institute investigator. Each of the peripheral genes has a small effect on the complex trait. But because those thousands of genes outnumber the core genes by orders of magnitude, most of the genetic variation related to complex diseases and other complex traits comes from the thousands of peripheral genes. So, ironically, the genes whose impact on complex disease is most indirect and small end up being responsible for most of the inheritance patterns of the complex disease. "This is a compelling paper that presents a plausible and fascinating model to explain a number of confusing observations from genome-wide studies of disease," said Joe Pickrell, PhD, an investigator at the New York Genome Center, who was not involved in the work.


Until recently, said Dr. Pritchard, he thought of genetically complex traits as conforming to a polygenic model, in which each gene has a direct effect on a trait, whether that trait is something like height or a disease, such as autism.
But last year, while putting together a paper on the recent evolution of height in northern Europeans, Dr. Pritchard was forced to rethink that idea.

In the earlier work on the genetics of height, Dr. Pritchard and his colleagues were surprised to find that essentially the entire genome influenced height. "It was really unintuitive to me," he said. "To be honest, I thought that it was probably wrong." His team spent a long time trying to understand the surprising result.

Instead, he said, "I gradually started to realize that the data don't really fit the polygenic model." That work led directly to the current Cell paper, he said. "We started to think, 'If the whole genome is involved in a complex trait like height, then how does that work?'"


The polygenic model leads researchers to focus on the short list of core genes that function in molecular pathways known to impact diseases. So, therapeutic research typically means addressing those core genes. A common approach to gene discovery is to do larger and larger genome-wide association studies, the paper notes, but Dr. Pritchard's team argues against this approach because the sample sizes are expensive and the thousands of peripheral genes uncovered are likely to have tiny, indirect effects. "After you get the first 100 hits," said Dr. Pritchard, "you've probably found most of the core genes you're going to get through genome-wide association studies."

Instead, he recommends switching to deep sequencing of the core genes to hunt down rare variants that might have bigger effects. For clinical use, Dr. Pritchard said, there's still a rationale for genome-wide association studies: to predict the peripheral gene-based risk factors in individual patients in order to personalize medicine.


Dr. Pritchard's omnigenic model promises to take basic biology in new directions and means biologists need to think a lot more about the structure of networks that link together those thousands of peripheral disease genes.

"If this model is right," said Dr. Pritchard, "it's telling us something profound about how cells work that we don't really understand very well. And so maybe that puts us a little bit farther away from using genome-wide association studies for therapeutics. But in terms of understanding how genetics encodes disease risk, it's really important to understand."

[Press release] [Cell abstract]