Skip to 0 minutes and 14 seconds In the last years there has been a lot of work in what is called Genome-Wide Association Studies or GWAS.
Skip to 0 minutes and 23 seconds In these studies, the idea is very simple: to gather a population of patients and a very similar population of normal individuals that may be used as control of this population (of patients), and then to look at the genome of both populations and see where in the genome there are discrepancies that could be related to the presence of the disease. The idea then is to gather lots of information on lots of patients looking really deep at the genome and then to do this analysis. In general so we have the two populations, the genome analysis on them and then statistical analysis.
Skip to 1 minute and 12 seconds In a simple case we can see that in a given one of the two populations -in the control or in the disease population- we have a higher frequency of a given variant in the genome. What means is that this variant could be at the base of causation of this different susceptibility and there are lots of statistical ways of dealing with this data. Imagine that in all the cases it’s a huge amount of data and in this association analysis we have many different diseases and traits, we have a very large number of individuals that we are looking deep in the genome.
Skip to 2 minutes and 5 seconds Then we have lots of statistics and at the very end we end up with a plot in which we can see the whole genome; and, in some places, we see that there are picks in which we see something unexpected in the sense that the frequency of these variants are much higher in one of the populations –let’s say in the populations of patients– meaning that it is very likely that in this portions of the genome there would be genes of susceptibility. In general, with that we are able to work out the cases in which diseases with high frequency are being dissected with variants in the genome that explain the susceptibility they may have.
Skip to 2 minutes and 59 seconds Here, in this plot you can see some of the examples in the diagonal going from the top left to the bottom right and in this case, you can see from the clear monogenic to the very complex cases in which the variants that are really at high frequency may account for diseases that are also at high frequency. The effect of these variants vary and the ideal is to find the variants that have a deeper, a very strong effect and right now, people working in the genetic of complex diseases are trying to find the ones that are already in the lower part, I mean in the susceptibility not being very, very strong.
How we know there is a heritability? Part 3
When we try to understand genetic diseases, we see that they often do not follow a single mode of inheritance.
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