This study examines the temporal and geographical evolution of polygenic scores (PGSs) across cognitive measures (Educational Attainment [EA], Intelligence Quotient [IQ]), Socioeconomic Status (SES), and psychiatric conditions (Autism Spectrum Disorder [ASD], schizophrenia [SCZ]) in various populations. Our findings indicate positive directional selection for EA, IQ, and SES traits over the past 12,000 years. Schizophrenia and autism, while similar, showed different temporal patterns, aligning with theories suggesting they are psychological opposites. We observed a decline in PGS for neuroticism and depression, likely due to their genetic correlations and pleiotropic effects on intelligence. Significant PGS shifts from the Upper Paleolithic to the Neolithic periods suggest lifestyle and cognitive demand changes, particularly during the Neolithic Revolution. The study supports a mild hypothesis of Gregory Clark’s model, showing a noticeable rise in genetic propensities for intelligence, academic achievement and professional status across Europe from the Middle Ages to the present. While latitude strongly influenced height, its impact on schizophrenia and autism was smaller and varied. Contrary to the cold winters theory, the study found no significant correlation between latitude and intelligence.

Genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment (EA) were used to test a polygenic selection model. Weighted and unweighted polygenic scores (PGS) were calculated and compared across populations using data from the 1000 Genomes (n = 26), HGDP-CEPH (n = 52) and gnomAD (n = 8) datasets. The PGS from the largest EA GWAS was highly correlated to two previously published PGSs (r = 0.96–0.97, N = 26). These factors are both highly predictive of average population IQ (r = 0.9, N = 23) and Learning index (r = 0.8, N = 22) and are robust to tests of spatial autocorrelation. Monte Carlo simulations yielded highly significant p values. In the gnomAD samples, the correlation between PGS and IQ was almost perfect (r = 0.98, N = 8), and ANOVA showed significant population differences in allele frequencies with positive effect. Socioeconomic variables slightly improved the prediction accuracy of the model (from 78–80% to 85–89%), but the PGS explained twice as much of the variance in IQ compared to socioeconomic variables. In both 1000 Genomes and gnomAD, there was a weak trend for lower GWAS significance SNPs to be less predictive of population IQ. Additionally, a subset of SNPs were found in the HGDP-CEPH sample (N = 127). The analysis of this sample yielded a positive correlation with latitude and a low negative correlation with distance from East Africa. This study provides robust results after accounting for spatial autocorrelation with Fst distances and random noise via an empirical Monte Carlo simulation using null SNPs.

We analyzed whole-genome sequencing (WGS) data from 51 populations and combined WGS and array data from 89 populations. Multiple types of polygenic scores (PGS) were employed, derived from multi-ancestry, between-family genome-wide association study (GWAS; MIX-Height), European-ancestry, between-family GWAS (EUR-Height), and European-ancestry siblings GWAS (SIB-Height). Our findings demonstrate that both genetic and environmental factors significantly influence adult body height between populations. Models that included both genetic and environmental predictors best explained population differences in adult body height, with the MIX-Height PGS and environmental factors (Human Development Index [HDI] + per capita caloric intake) achieving an R² of .83. Our findings shed light on Deaton’s ‘African paradox’, which noted the relatively tall stature of African populations despite poor nutrition and childhood health. Contrary to Deaton’s hypotheses, we demonstrate that both genetic differences and environmental factors significantly influence body height in countries with high infant mortality rates. This suggests that the observed tall stature in African populations can be attributed, in part, to a high genetic predisposition for body height. Furthermore, tests of divergent selection based on the Q_ST (i.e., standardized measure of the genetic differentiation of a quantitative trait among populations) and F_ST (neutral marker loci) measures exceeded neutral expectations, reaching statistical significance (p < .01) with the MIX-Height PGS but not with the SIB-Height PGS. This result indicates potential selective pressures on body height-related genetic variants across populations.

This study explores directional selection on physical and psychosocial phenotypes in Eastern Eurasian populations, utilizing a dataset of 1245 ancient genomes. By analyzing polygenic scores (PGS) for traits including height, educational attainment (EA), IQ, autism, schizophrenia, and others, we observed significant temporal trends spanning the Holocene era. The results suggest positive selection for cognitive-related traits such as IQ, EA and autism spectrum disorder (ASD), alongside negative selection for anxiety and depression. The results for height were mixed and showed nonlinear relationships with Years Before Present (BP). These trends were partially mediated by genetic components linked to distinct ancestral populations. Regression models incorporating admixture, geography, and temporal variables were used to account for biases in population composition over time. Latitude showed a positive effect on ASD PGS, EA and height, while it had a negative effect on skin pigmentation scores. Additionally, latitude exhibited significant nonlinear effects on multiple phenotypes. The observed patterns highlight the influence of climate-mediated selection pressures on trait evolution. Spline regression revealed that several polygenic scores had nonlinear relationships with years BP. The findings provide evidence for complex evolutionary dynamics, with distinct selective pressures shaping phenotypic diversity across different timescales and environments.

This is the first paper to report evidence of a cross-population genetic correlation between educational attainment and IQ. Principal component analysis (PCA) was used to identify the underlying genetic structure resulting from recent (after the out of Africa migration, about 60Kya) directional selection. Converging evidence from two different genetic databases (1000 Genomes and ALFRED, comprising 14 populations and 8 racial groups, respectively) and two independent sets of genes (14 in total) found by GWAS to have a significant association with IQ and Educational Attainment, reveals a high correlation (around 0.9) between these two social science constructs across populations and ethnic groups. This correlation in turn provided convergent validity for the genetic measures identified with PCA. Two alleles associated with higher intracranial volume were positively correlated to the two PCs. A separate analysis carried out on an independent set of alleles related to human stature suggests that this trait was subject to different directional selective pressures and provided evidence for the discriminant validity of alleles supposedly related to IQ and educational attainment. One-way ANOVA showed that the average frequencies of height increasing alleles for three racial groups (East Asian, Sub-Saharan African and European) differed significantly and that Africans had significantly higher frequencies than East Asians. A significant negative genetic correlation (r around 0.9) between height and intelligence was found at a cross-population level, contrasting the generally positive correlation found within populations. Evolutionary explanations in terms of Allen’s rule and the theory of cold winters are attempted. The GWAS hits for height were from studies carried out on different ethnic groups, and the converging results suggests that the same genes have similar effects across racial groups. This paper provides evidence that Principal Component Analysis and ANOVA can be used to detect deviations from random drift and detect directional selection on polygenic traits in recent human evolutionary history.