Tiffany, Liles, Liver Cancer discussed on This Week in Science
There's a micro Buyum of Amarna and our as and motor proteins, and all sorts of other smaller actors that are causing. Downstream, whichever direction, you look that, that we hadn't occurred to us are the motivators for how things actually function. So we are as we are just scratching the surface of nutrition when it comes to the microbiome, we're just actually scratching the surface of genomics, because there's a whole bigger more complicated layer beneath just the genes themselves. And I think one of the things that because we study sex differences, Bradley one of the first questions I think it is about how do you how do you know that sex chromosomes versus hormones? So we know especially there's large differences testosterone in androgen, and estrogen progesterone. And, and so are aren't the two is completely linked together, if you're ex than you're going to have this set of hormones, and if you're way, have this in turns out that's really not true at all. And we see differences in, gene. Expression on the X Y during development the four you even have gone ads developing. So now we have this added layer where we have? Excellent, y have their own unique, gene expression than those are modulated just like everything else, Gino by Andrew Jans. Estrogens. And then there's cross talk. So it's kind of this wonderful symphony, and we just have to pick apart. You know what's the violin contributing, and what's the cello contributing, and where the Tiffany, drums, right? Like where are all these things? And that's what we're trying to do. Now to me, that's I don't think it's that we're not finding the things we just have to listen and try to tease apart those different aspects. Do you think with the amount of variation that there is inherent in the human genome that, you know that we will eventually get beyond the single, single, gene, single variant kind of system? Do you think with bioinformatics? Are we going to be able to eventually really address like the multi multi-layered multifactorial aspect of the problem one hundred percent? I think that's where we're going now that's where the leading edge of buying for Matic's into Nomex is. Going is trying to figure out how do we look for networks of interacting genes and not even just interacting genes, but interacting Eissa forms. So interacting variants of the gene, so not into only of so for G rating different illegals, then you can have a different sets of Exxon's together. Sorry, I'm getting too complicated. But right. So how do we how do we look at the variants of the gene, had we look particularly -tations in, gene? How do they look at how those are interacting with our hormones with our environment with our nutrition with stress? It's not going to be solved in our lifetime or, or ever. I'm going to say you know what come back to me when I die and tell me if I'm wrong. But. But, but I think we're making headway on it, and we're trying to what too late. I mean, it'd be really one sided conversation. So maybe will perfected the brain in a jar stuff that we were weeks ago. And then it'll be fine, we tape and not. But we're trying to figure out into it was like I you're leaving me hanging, now we're really trying to some of the things we're working on right now is to look at not only the mutation being associated with disease phenotype, for example, one of the things looking at his liver cancer, and sex differences in liver cancer. But we're looking at. The interaction of that, gene, that eleo with other Liles. And then every possible combination of Liles. So those sets of combinations get extra nominal really fast. And it used to be impossible to do that kind of computing. But we're, we're starting to get to be there, for example at a meeting of years ago. There was a large project called the human a thousand genomes project, which eventually ended up sequencing more than two thousand people and it took, you know multiple apps. Many years and tons of compute time and Google because they could decided to redo the whole project and tell us how fast in wonderful..