Conversation with Greg Gibson. Part 1

No doubt, the genetic of complex traits is one of the most challenging points in biology and in genetics today; because it has a lot of implications, not only in its understanding, but also in the applications. Today we have with us Greg Gibson, he is professor and director of the Center for Integrative Genomics in the School of Medicine, in Emory University in Atlanta, in USA. He was trained as a geneticist in Sidney University, and then he worked in Basel, and then also in Stanford, and he was professor at the School of Biology at Georgia Tech since 2009. His research focuses on broad interest areas on quantitative genetics, quantitative evolutionary genetics.

The understanding of susceptibility using also not only DNA sequences but transcriptomics, and trying to understand how this expression profiles may be related to genomics, but with a very clear applied interest in health. In this interview, we are going to focus on complex traits, but mainly on its importance, what is today called the personalized medicine, or personalized genomic medicine. Both in, what is called, precision medicine and what Greg has coined as predictive health. Meaning that using the knowledge we have on complex traits, not only to understand the genetic of complex traits, but to be used for improving our health. Greg, genetics is providing lots of new results in the dissection of complex traits.

Diseases, like diabetes, obesity, psychiatric disorders and what is used in general, is what is called the GWAS or the genome-wide association studies. Is this track fruitful? Are we learning things? It is worth going in this way? First of all thank you very much for inviting me here today at this beautiful setting. It’s a fabulous to be here.

You know, I’m a really big fan of GWAS. I think it’s really revolutionized, and I use that word not too carefully. It’s revolutionized our understanding of genetics. I think I was lucky enough when I was studying in Basel, 30 years ago, to be part of the revolution that understood how genes regulate development, and now 25 years later, we’ve had a new revolution, about understanding how quantitative genetic works. How genes throughout the genome regulate disease, and evolution, and so much about who we are.

You know, Peter Visscher is one of the latest of the field, he wrote a review with Mark McCarthy 5 years ago, after 5 years, and they said for the cost of about an aircraft carrier, so about a quarter of a billion dollars, we’ve found thousands of genes influencing a wide range of complex traits. And I argue that it was an enormously productive investment, and I can’t agree more. Compared to the way we did it thirty years ago, forty years ago, it’s so much more powerful, so much more illuminating. And I think the most important thing it’s done, it is really distinguish between three models that existed for the genetics of complex traits.

So one was common disease, common variants; was the idea that every disease, diabetes, cancer, whatever it was, had about 20 to 50 genes that were important, and each one of them would explain maybe 5% of the variation. It turns out that’s just not the case. So the two alternatives left are something called (rare diseases of large effect) rare alleles of large effect. So if you came from psychiatric genetics or early onset congenital disorders, people will say that… look, every different case is a different case, with a different mutation, in aging, and if you hadn’t that mutation, you won’t have the disease.

The other viewpoint was called the infinitesimal model, which is that there are, in fact, thousands of genes in front every single trait, and they have very, very small effects. Maybe an effect as small as a tenth of a millimeter of height or an extra day of staying in school. And now I think it’s absolutely clear that the infinitesimal model is winning out, across all of the different classes of diseases and complex traits. So that’s a very profound understanding because it tells us that the genetics is so much more complicated that we ever thought before.