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Showing posts with the label quantitative traits

What do GWAS signals mean?

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Genome-wide association studies ( GWAS ) have been highly successful at linking genetic variation in hundreds of genes to an ever-growing number of traits or diseases. The fact that the genes implicated fit with the known biology for many of these traits or disorders strongly suggests (effectively proves, really) that the findings from GWAS are “real” – they reflect some real biological involvement of those genes in those diseases. (For example, GWAS have implicated skeletal genes in height, immune genes in immune disorders, and neurodevelopmental genes in schizophrenia). But figuring out the nature of that involvement and the underlying biological mechanisms is much more challenging. In particular, it is not at all straightforward to understand how statistical measures derived at the level of populations relate to effects in individuals. Here, I explore some of the diverse mechanisms in individuals that may underlie GWAS signals. GWAS take an epidemiolo...

No gene is an island

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Source Many people, scientists and non-scientists alike, object to what they perceive as genetic determinism . This is often a reaction to geneticists apparently over-reaching and claiming that some trait or condition is “caused by” a single gene. A common rejoinder is that any biological process obviously involves many hundreds of gene products, interacting with each other in complex ways and so it is nonsense to say that the trait is determined by a single gene. That is absolutely true, if you are using the word “gene” purely in the molecular biology sense – as a piece of DNA that encodes a particular product (usually a protein). But geneticists also use it in the original sense, as a unit of heredity – a genetic variant or mutation that can be passed on across generations and that influences some phenotype. Genetics is not about how a characteristic arises, it is about how variation in that characteristic arises. For example, when you are describing someone, you m...