"Neandertal variants have been hypothesized to influence many phenotypes in AMHs, including lipid metabolism, immunity, depression, digestion, hair, and skin, on the basis of the enrichment of Neandertal variants in regions of the genome relevant to these traits. Accordingly, we first tested these hypotheses using genome-wide complex trait analysis (GCTA) to estimate the phenotypic risk explained by 1495 genotyped common (minor allele frequency > 1%) Neandertal SNPs for a set of 46 highprevalence phenotypes from the hypothesized categories, using age, sex, and eMERGE site as covariates."
When testing these 46 traits they controlled the FDR < 0.05 (false discovery rate). Then they replicated the associations in an independent sample.
The effect sizes are pretty small (1-2%), so having the explanatory variants won't have much bearing whether or not you'll get these complex traits.
I'm also curious as to why ethnic origin wasn't a covariate.
So if any correlations were found, they basically did another study to replicate it. And that's a big sample size too. Many studies are published with far weaker correlations.
It's possible this study is novel mainly for the methodology, which as reported is the first wide-scale test of its nature. The media of course focus on the correlations because they are more sensational - it gets people thinking "am I depressed because I'm part neanderthal?"
I agree it's meaningless, in the sense that we have no idea what the cause is. It could be indirect, it could be random rather than anything special about neanderthals, it could be confounded with ethnicities that have higher neanderthal DNA, etc.
(Also, the base rate of depression is far more than 1%, see e.g. http://tech.mit.edu/V120/N3/dep1.3n.html - it's around 17% for just a major depressive episode.)
Does anyone know how they compensated the statistics to control for the p-hacking?