From BioRxiv (i.e., not yet peer reviewed):

Screening human embryos for polygenic traits has limited utility Ehud Karavani, Or Zuk, Danny Zeevi, Gil Atzmon, Nir Barzilai, Nikos C. Stefanis, Alex Hatzimanolis, Nikolaos Smyrnis, Dimitrios Avramopoulos, Leonid Kruglyak, Max Lam, Todd Lencz, Shai Carmi Genome-wide association studies have led to the development of polygenic score (PS) predictors that explain increasing proportions of the variance in human complex traits. In parallel, progress in preimplantation genetic testing now allows genome-wide genotyping of embryos generated via in vitro fertilization (IVF). Jointly, these developments suggest the possibility of screening embryos for polygenic traits such as height or cognitive function. There are clear ethical, legal, and societal concerns regarding such a procedure, but these cannot be properly discussed in the absence of data on the expected outcomes of screening. Here, we use theory, simulations, and real data to evaluate the potential gain of PS-based embryo selection, defined as the expected difference in trait value between the top-scoring embryo and an average, unselected embryo. We observe that the gain increases very slowly with the number of embryos, but more rapidly with increased variance explained by the PS. Given currently available polygenic predictors and typical IVF yields, the average gain due to selection would be ≈2.5cm if selecting for height

Or about an inch.

, and ≈2.5 IQ (intelligence quotient) points if selecting for cognitive function.

From about the 50th percentile to about the 57th percentile.

These mean values are accompanied by wide confidence intervals; in real data drawn from nuclear families with up to 20 offspring each, we observe that the offspring with the highest PS for height was the tallest only in 25% of the families. We discuss prospects and limitations of PS-based embryo selection for the foreseeable future.

On the other hand the state of the art PGS for IQ-related “educational attainment” (Lee et al, 2018) is only up to 11% of variance at present. Lee and Co. used a staggering sample size of 1.1 million, but meta-analyses with sample sizes into the billions are conceivable within a few decades. (Educational attainment data is somewhat easier to obtain for huge sample sizes since a huge number of medical records forms ask about it somewhere. People aren’t completely reliable about recounting their educational attainment to their doctors, but they are more reliable than estimating their IQs, so IQ research usually requires giving at least a brief test to patients. Hence, it’s rarer.)

This paper notes:

To date, the largest GWAS of intelligence [10,11] has demonstrated a relatively modest out-of-sample 𝑟ps (≈5%), despite large sample sizes (n≈300,000 individuals). By contrast, recent large-scale GWASs of height have attained 𝑟ps 2 of approximately 25%, while demonstrating a highly polygenic genetic architecture similar to intelligence[12]. … For example, doubling the proportion of explained variance of height from ≈25% to 50% is expected to increase the mean gain from ≈3 to ≈4.24cm, with a maximum possible gain of ≈5.5cm for 𝑟ps2 ≈80% (the upper bound of the heritability of the trait, as derived from twin studies;[29]). Similarly, quadrupling the variance explained for IQ would lead to a doubling of the gain, to ≈6 IQ points (given 𝑛 = 10 embryos).

So if they could get variance of IQ explained up to about 1.5x to 2x the level of educational attainment variance explained a year ago by Lee, they are talking about 6 IQ points, or from the 50th percentile to 66th percentile.

This is for selecting from 10 embryos. If they could somehow go to 1000 embryos, they could get to about 10 IQ points.