Jonathan Pritchard (center) and his colleagues, Yang Li (left) and Evan Boyle, discuss their recent work positing that almost any gene can influence disease.
Steve Fisch
Thousands of genes influence most diseases
In a provocative new perspective piece, Stanford researchers say that disease genes are spread uniformly across the genome, not clustered in specific molecular pathways, as has been thought.
A core assumption in the study of 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 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 paper published June 15 in Cell. Jonathan Pritchard, 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 researchers call their provocative new understanding of disease genes an “omnigenic model” to indicate that almost any gene can influence diseases and other complex traits. In any cell, there might be 50 to 100 core genes with direct effects on a given trait, as well as easily another 10,000 peripheral genes that are expressed in the same cell with indirect effects on that trait, said Pritchard, who is also a Howard Hughes Medical Institute investigator.
Each of the peripheral genes has a small effect on the trait. But because those thousands of genes outnumber the core genes by orders of magnitude, most of the genetic variation related to diseases and other traits comes from the thousands of peripheral genes. So, ironically, the genes whose impact on disease is most indirect and small end up being responsible for most of the inheritance patterns of the disease.
“This is a compelling paper that presents a plausible and fascinating model to explain a number of confusing observations from genomewide studies of disease,” said Joe Pickrell, PhD, an investigator at the New York Genome Center, who was not involved in the work.
From a polygenic to omnigenic model
Until recently, said 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.
Jonathan Pritchard
But last year, while putting together a paper on the recent evolution of height in northern Europeans, Pritchard was forced to rethink that idea.
In the earlier work on the genetics of height, 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?’”
Therapeutic implications
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 genomewide association studies, the paper notes, but 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 Pritchard, “you’ve probably found most of the core genes you’re going to get through genomewide association studies.”
Instead, he recommends switching to deep sequencing the core genes to hunt down rare variants that might have bigger effects. For clinical use, Pritchard said, there’s still a rationale for genomewide association studies: to predict the peripheral gene-based risk factors in individual patients in order to personalize medicine.
Implications for basic science
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 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 further away from using genomewide association studies for therapeutics. But in terms of understanding how genetics encodes disease risk, it’s really important to understand.”
Learn more:Thousands of genes influence most diseases
The Latest on: Disease genes
- Huntington's disease driven by slowed protein-building machinery in cellson March 5, 2021 at 10:04 am
In 1993, scientists discovered that a single mutated gene, HTT, caused Huntington's disease, raising high hopes for a quick cure. Yet today, there's still no approved treatment.
- Shared genetic etiology between Parkinson’s disease and blood levels of specific lipidson March 5, 2021 at 3:51 am
Parkinson’s disease (PD) is characterized by the degeneration of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies. The mechanisms underlying these molecular and cellular ...
- Fauna Bio Awarded Grant from National Institute of Health to Find New Treatments for Human Diseases by Studying the Genes of Animalson March 4, 2021 at 8:09 am
Fauna Bio today announced it has received a grant from the National Human Genome Research Institute (NHGRI) to investigate new ways to treat human diseases by studying the genetic makeup of other ...
- Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins | European Journal of Human Geneticson March 4, 2021 at 2:00 am
Polycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are ...
- Dietary Supplement Reverses Effects of Alzheimer’s Disease APOE4 Risk Gene on Lipid Metabolismon March 3, 2021 at 9:00 pm
MIT team hopes that findings will lead to clinical studies to see if choline can help protect against AD in people who carry the APOE4 gene.
- Study shows loss of function of PLD1 gene is causal to congenital heart diseaseon March 2, 2021 at 5:05 am
A team of researchers co-led by Michael Frohman, MD, Ph.D., of Stony Brook University, has identified an important cause of congenital heart disease. They discovered that certain loss of functions in ...
- Loss of functions in the PLD1 gene causes congenital heart diseaseon March 1, 2021 at 9:36 pm
A team of researchers co-led by Michael Frohman, MD, PhD, of Stony Brook University, has identified an important cause of congenital heart disease.
- Tenaya grabs $106M top-up to push heart disease gene therapies to the clinicon March 1, 2021 at 5:00 am
With another $106 million in the bank, heart-focused Tenaya Therapeutics is ready to talk targets. The series C funding will propel several preclinical programs toward the clinic, including a gene ...
- Genes identified that increase the risk of obesity but also protect against diseaseon February 26, 2021 at 12:09 pm
Scientists have identified 62 genes that lead to both higher levels of body fat but a lower risk of cardiovascular and metabolic diseases. These genes may help to keep body fat healthy, and open a new ...
- Genes Linked to Coronary Artery Disease Risk Act through the Liveron February 26, 2021 at 5:00 am
An integrative genomics approach can help identify putative causal regulatory regions and target genes that could predispose to clinical manifestation of coronary artery disease by affecting liver ...
via Google News and Bing News