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Hello. Um Anyone there? Yeah, hi. Sorry about that, Ana J. Um, welcome everyone to the next like pom crash course lecture. Um Are you, is everything working fine for you? Are you fine to share your slides? All right, bye bye always. I am. Yeah. Although for some reason I can't seem to upload down to medal medal, so I'll just share a whole screen if that's all right. That's fine. Yeah, some of the other lights had problems with that as well. All right. Uh Just remember if you are sharing your entire screen, just check the chart every sort of periodically. Yeah, I can see that. So can everyone see it? Uh So if we begin? Uh, hi, my name's, I'm a second year medical student and we're doing genetics. I know this is something that a lot of people keep to the end. So, hello to anyone who's doing this a night before at two times speed. Let's crack on. So we'll be covering complex disease and pharmacogenetics. Uh That's probably the longest one at the moment. High yield one, everyone's working up now. Er, emerging treatments isn't that important? But you've gotta know some of the main uh drugs that are used and brittle bone, which is more of a revision of everything in pom and integrating a lot of other stuff together. Uh So complex disease and pharmacogenetics. Uh This is stuff that you would have learned in basic a level biology if you did it. But it's the idea that uh men delaying traits or anything, which is a single gene, anything highlighted in red, by the way, is something you need to know and could come up under the exam. Uh So it's easy if you're going over this at the end, uh it will be directly. Uh How should I put it following the gene and phenotype pattern? Think of the pea plants. If there's a gene that influences the height or the color, that will be the direct relationship, there, nothing confounding or making it different. Uh An example that in humans is having dimples whereas complex traits are two or more genes and also environmental factors. Uh they're harder to track and harder to identify using genome sequencing. Uh And here are a couple of examples, height weight, BP and intelligence. And an example of a disease which is a, which has a complex trait is uh cardiovascular disease. Uh And even though we have two separations, in reality, there's quite a significant um spectrum between them. Some traits are more lay, some are more complex. Uh and are all normally affected or most of them are affected by the environment or epigenetics. Now, heritability, you gotta know the definition if you want to write it down now. Uh But it's essentially how much are gene responsible for the difference in the human population. That's about it. You guys should know what dizygotic and monozygotic twins are but a quick recap. Dizygotic two eggs, two zygotes uh that have been fertilized independently. Monozygotic twins are one egg being fertilized by one sperm and then split it into two zygotes. And therefore, monozygotic twins theoretically have 100% of the same genes and therefore be exactly the same. But that's not the case. And here we have uh uh some monozygotic and dizygotic studies showing relationship between intelligence and uh between the two, between the two twins and sleep time. And as we can see, I, the intelligence is a bit more linear whereas the sleep times is all over the place, that's what we call discordant and non er discordant and uh concordant. But so the higher one here is moderate to high heritability if it's following a linear pattern. Whereas anything which is clustered is sort of a low ability, heritability. And yeah, like I mentioned, we have concordance. Both uh pairs have a trait which is almost linear uh when one individual and the pair has a trait and the other doesn't, then they're discordance. All right. Uh And therefore, if something is 99% concordant, we would say that that's mostly influenced by genetics, but there is always some sort of environmental influence and it's very rare to have 100% out of a mandelay in trait, which is entirely genetically uh decided. So here's some high your content and you guys should remember this. But as you said, theory isn't really what we see in practice and we have things called single n er single nucleotide polymorphisms, which we believe should be accounting for all of the polymorph, all of the human diseases that we have uh due to mutations, single nucleotide polymorphisms being just one of those act eg um nucleotides being replaced, but that's not true. And half of our genetic diseases uh are unaccounted for. And here are some of the reasons why and honestly, these are a bit of common sense um along with just knowing why there could be uh differences in ge in genetic diseases. The first one is the idea of rare variant variants accumulating and that's why they're hard to identify uh if you have S MPS with which are very hard to find, but they accumulate together, they add to make it even bigger phenotype, then you miss them when you're my epigenetics, uh screening systems not being as efficient as we think they are. And often we have these low frequency S MPS which also only have an intermediate effect, they don't completely stop or start a disease. Uh But they would have a sort of middle ground which is also hard to identify, especially when you're screen for disease. So, here's a nice table and I'm not gonna read through it entirely. But, uh, the idea of genetic association studies, essentially reading the human genome as a book. And you're looking for a specific, um, how should I put it a specific spelling mistake? Let's look at, like, look at it like that when you've got c, uh, candidate gene association studies, that's the idea of knowing around what chapter the, er, spelling mistake would be. And that's why it's hypothesis driven. Uh, we're looking for a certain gene or a certain group of genes, uh, which we know would probably have it and therefore trying to find our spelling mistake, our SNP in that, but that has the problems of being biased towards these known genes. So we can't discover anything new or a new, er, spelling mistake. And, er, the benefits are therefore, we're not looking through the entire book. It's wasting a lot of time and money. Whereas genome wide association studies is, imagine we have a lot of these books published, uh, publicized, uh which is our genomes in the human population and people have already looked through them and have found a lot of different spelling mistake within lots of different chapters. So we know the most common chapters that would have these S NPS. So therefore we can find an, I guess, HN search a bit more but it's wider than the candidate gene association studies. And G US is what we use most commonly. Uh However, once again, they don't uh look at environmental influences or epigenetics and they won't find very rare areas because we're looking at things which have already been uh studied before. Uh However, they are useful when it comes to er, er new mechanisms. Because when you're looking through these previously studied er, genomes, we have been able to identify new mu mutations which could be more useful in the future. And whole genome sequencing is a lot more costly and a lot more uh time wasting. But uh it looks through the entire book checking all 6 billion bases and it's hypothesis free therefore and can find every single S MP in an individual and every noncoding regions, er everything which is epigenetic.