Genetic Predictions: It’s Complicated

Various innovations in the field of genomics over the past few decades have given researchers hope that resolutions to long-lasting debates might finally be on the horizon. In particular, many have become optimistic about the prospects for disentangling the threads of “nature” and “nurture”—that is, about determining the extent to which genes alone can explain differences within and between populations.

But two recent studies are now calling some of the methods underlying those aspirations into question.

A key breakthrough was the recent development of genome-wide association studies (GWAS, commonly pronounced “gee-wahs”). The genetics of simple traits can often be deduced from pedigrees, and people have been using that approach for millennia to selectively breed vegetables that taste better and cows that produce more milk. But many traits are not the result of a handful of genes that have clear, strong effects; rather, they are the product of tens of thousands of weaker genetic signals, often found in noncoding DNA. When it comes to those kinds of features—the ones that scientists are most interested in, from height, to blood pressure, to predispositions for schizophrenia—a problem arises. Although environmental factors can be controlled in agricultural settings so as not to confound the search for genetic influences, it’s not so straightforward to extricate the two in humans.

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