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Showing posts with the label SNPs

Eugenics, statistical hubris, and unknowable unknowns in human genetics

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A new paper just out in Nature , by Peter Visscher and colleagues (including bio-ethicist Julian Salvulescu) explores the idea of polygenic genome editing of human embryos to reduce the risk of common diseases. This is, to say the least, a controversial idea, and a decidedly fantastical one. The authors present the results of statistical modelling which suggests that editing a small number of risk variants in each embryo’s genome could dramatically reduce the risk of a number of common disorders. But there are good reasons (lots of them) to doubt the assumptions on which this modelling is based and to have serious concerns about possibly deleterious unintended consequences of such interventions. I co-wrote a commentary on the article with geneticist Shai Carmi and law professor and bio-ethicist Hank Greely, outlining some of the limitations of the modelling and our concerns over the dangers of the proposed approach. I’ll expand on those points here.   First, the development...

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...