Top Ten New York Times Bestselling Author
AI Summary. Ancient DNA analysis of nearly 16,000 West Eurasians reveals that hundreds of alleles underwent strong directional selection over the past 10,000 years, shifting genetic predictors of body fat, schizophrenia risk, and cognitive performance by amounts equivalent to one standard deviation of modern variation.
Core argument: Analysis of 15,836 West Eurasians detected directional selection across 9.7 million variants, revealing that alleles for light skin pigmentation increased.
We present a method for detecting directional selection in ancient DNA time-series data that tests for consistent trends in allele frequency change over time, and apply it to 15,836 West Eurasians (10,016 with new data). We estimate selection coefficients at 9.7 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits. We focused on 12 traits of particular interest with significant signals from all three tests (Figure 4). One of the strongest signals is an increase over time in the PGS for light skin pigmentation. Type 2 diabetes risk factors give compelling signals of negative selection. We detected negative polygenic selection against alleles associated today with psychoses such as bipolar disorder and schizophrenia. We finally observed signals of selection for combinations of alleles that today are associated with three correlated behavioural traits: scores on intelligence tests, household income and years of schooling. An important caveat is [that] these effects were measured in industrialized societies, and it remains unclear how these relate to phenotypes that were adaptive in the past.New paper from Science Advances highlights the replication problem in science, “….We use publicly available data to show that published papers in top psychology, economics, and general interest journals that fail to replicate are cited more than those that replicate. This difference in citation does not change after the publication of the failure to replicate. Only 12% of post replication citations of nonreplicable findings acknowledge the replication failure. Existing evidence also shows that experts predict well which papers will be replicated. Given this prediction, why are nonreplicable papers accepted for publication in the first place? A possible answer is that the review team faces a trade-off. When the results are more “interesting,” they apply lower standards regarding their reproducibility….”
Core result, “…Our main finding is that papers that fail to replicate in (5-7) are cited more than those that are replicable. We find no significant change in citation trends, even after the publication of the failed replication. Notably, only a minority of publications after the failed replications were published acknowledge the failure. The “quality” of citations of papers that failed to replicate is similar to that of papers that were replicated: We do not find a difference in how often the citations of nonreplicable publications are cited by others or in the impact factor of the journals in which citations are published…”
The evidence, "...Figure 1 shows the distribution of total citation counts by the end of 2019 of the papers included in the replication projects, separately depending on replicability for Nature/Science, economics journals, and psychology journals. Replicability is measured according to the criterion that the replication project featured a P value of 0.05 or lower in a two-sided test, with an effect in the same direction as the original test….”
