theatlantic | In 1999, a group of scientists scoured the genomes of around 150 pairs of siblings in an attempt to find genes that are involved in autism.
They came up empty. They reasoned that this was because the risk of
autism is not governed by a small number of powerful genes, which their
study would have uncovered. Instead, it’s likely affected by a large
number of genes that each have a small effect. Perhaps, they wrote,
there might be 15 such genes or more.
But Evan Boyle, Yang Li, and Jonathan Pritchard from Stanford University think that this framework doesn’t go far enough.
They note that researchers often assume that those thousands of weakly-acting genetic variants will all cluster together in relevant genes.
For example, you might expect that height-associated variants will
affect genes that control the growth of bones. Similarly,
schizophrenia-associated variants might affect genes that are involved
in the nervous system. “There’s been this notion that for every gene
that’s involved in a trait, there’d be a story connecting that gene to
the trait,” says Pritchard. And he thinks that’s only partly true.
Yes,
he says, there will be “core genes” that follow this pattern. They will
affect traits in ways that make biological sense. But genes don’t work
in isolation. They influence each other in large networks, so that “if a
variant changes any one gene, it could change an entire gene network,”
says Boyle. He believes that these networks are so thoroughly interconnected that every gene is just a few degrees of separation away from every other. Which means that changes in basically any gene will ripple inwards to affect the core genes for a particular trait.
The Stanford trio call this the “omnigenic model.” In the simplest terms, they’re saying that most genes matter for most things.
