Genetic contributions to variation in human stature in prehistoric Europe Samantha L. Coxa, Christopher B. Ruffb, Robert M. Maierc,d,e, and Iain Mathiesona,1 aDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; bCenter for Functional Anatomy and Evolution, Johns Hopkins University School of Medicine, Baltimore, MD 21205; cProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142; dStanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142; and eAnalytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114 Edited by Richard G. Klein, Stanford University, Stanford, CA, and approved September 11, 2019 (received for review June 20, 2019) The relative contributions of genetics and environment to temporal Height is highly heritable (10–14) and therefore amenable and geographic variation in human height remain largely unknown. to genetic analysis by GWAS. With sample sizes of hundreds of Ancient DNA has identified changes in genetic ancestry over time, thousands of individuals, GWAS have identified thousands of but it is not clear whether those changes in ancestry are associated genomic variants that are significantly associated with the with changes in height. Here, we directly test whether changes over phenotype (15–17). Although the individual effect of each of these the past 38,000 y in European height predicted using DNA from variants is tiny [on the order of ±1 to 2 mm per variant (18)], their 1,071 ancient individuals are consistent with changes observed in combination can be highly predictive. Polygenic risk scores (PRS) 1,159 skeletal remains from comparable populations. We show that constructed by summing together the effects of all height-associated the observed decrease in height between the Early Upper Paleolithic variants carried by an individual can now explain upwards of 30% and the Mesolithic is qualitatively predicted by genetics. Similarly, of the phenotypic variance in populations of European ancestry both skeletal and genetic height remained constant between the (16). In effect, the PRS can be thought of as an estimate of “genetic Mesolithic and Neolithic and increased between the Neolithic and height” that predicts phenotypic height, at least in populations Bronze Age. Sitting height changes much less than standing height— closely related to those in which the GWAS was performed. One consistent with genetic predictions—although genetics predicts a major caveat is that the predictive power of PRS is much lower in small post-Neolithic increase that is not observed in skeletal remains. other populations (19). The extent to which differences in PRS Geographic variation in stature is also qualitatively consistent with between populations are predictive of population-level differences ANTHROPOLOGY genetic predictions, particularly with respect to latitude. Finally, in phenotype is currently unclear (20). Recent studies have dem- we hypothesize that an observed decrease in genetic heel bone onstrated that such differences may partly be artifacts of correlation mineral density in the Neolithic reflects adaptation to the de- between environmental and genetic structure in the original GWAS creased mobility indicated by decreased femoral bending strength. (21, 22). These studies also suggested best practices for PRS This study provides a model for interpreting phenotypic changes comparisons, including the use of GWAS summary statistics from predicted from ancient DNA and demonstrates how they can be large homogenous studies (instead of metaanalyses), and replica- combined with phenotypic measurements to understand the rela- tion of results using summary statistics derived from within-family tive contribution of genetic and developmentally plastic responses analyses that are robust to population stratification. to environmental change. Bearing these caveats in mind, PRS can be applied to ancient populations thanks to recent technological developments that have stature | height | ancient DNA | evolution dramatically increased aDNA sample sizes. These have provided remarkable insights into the demographic and evolutionary history – tature, or standing height, is one of the most heavily studied of both modern and archaic humans across the world (23 25), Shuman phenotypes. It is easy to measure in living individ- uals and relatively straightforward to estimate from skeletal Significance remains. As a consequence, geographic variation and temporal changes in stature are well documented (1–3), particularly in Measurements of prehistoric human skeletal remains provide a western Europe, where there is a comprehensive record of record of changes in height and other anthropometric traits prehistoric changes (4). The earliest anatomically modern hu- over time. Often, these changes are interpreted in terms of mans in Europe, present by 42,000 to 45,000 y before present plastic developmental response to shifts in diet, climate, or (BP) (5, 6), were relatively tall (mean adult male height in the other environmental factors. These changes can also be genetic Early Upper Paleolithic was ∼174 cm). Mean male stature then in origin, but, until recently, it has been impossible to separate declined from the Paleolithic to the Mesolithic (∼164 cm) be- the effects of genetics and environment. Here, we use ancient fore increasing to ∼167 cm by the Bronze Age (4, 7). Height can DNA to directly estimate genetic changes in phenotypes and to respond rapidly in a developmentally plastic manner to changes identify changes driven not by genetics, but by environment. in environment, as demonstrated by large increases in Europe, We show that changes over the past 35,000 y are largely pre- and worldwide, during the secular trends of the 19th and 20th dicted by genetics but also identify specific shifts that are more centuries (1, 4). In European countries today, mean adult male likely to be environmentally driven. height is ∼170 to 180 cm (1). It is broadly agreed that pre- historic changes were likely to have been driven by a combi- Author contributions: S.L.C., C.B.R., R.M.M., and I.M. designed research, performed re- nation of environmental (e.g., climate or diet) and genetic search, analyzed data, and wrote the paper. factors including drift, admixture, and selection (4, 7–9), al- The authors declare no competing interest. though the effects of these variables cannot be separated based This article is a PNAS Direct Submission. on skeletal data alone. In this study, by combining the results This open access article is distributed under Creative Commons Attribution-NonCommercial- of genome-wide association studies (GWAS) with ancient DNA NoDerivatives License 4.0 (CC BY-NC-ND). (aDNA), we directly estimate the genetic component of stature 1To whom correspondence may be addressed. Email: [email protected]. and test whether population-level skeletal changes between This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. ∼35,000 and 1,000 BP are consistent with those predicted 1073/pnas.1910606116/-/DCSupplemental. by genetics. www.pnas.org/cgi/doi/10.1073/pnas.1910606116 PNAS Latest Articles | 1of9 Downloaded by guest on September 27, 2021 particularly in Europe, and allow us to track the evolution of Early Upper Paleolithic (>25,000 BP) (EUP), Late Upper Paleo- variants underlying phenotypes ranging from pigmentation to diet lithic (25,000 to 11,000 BP) (LUP), Mesolithic (11,000 to 5500 BP), (26–29). In principle, PRS applied to ancient populations could Neolithic (8500 to 3900 BP), and post-Neolithic (5000 to 1100 BP, similarly allow us to make inferences about the evolution of including the Copper and Bronze Ages, plus later periods), re- complex traits. A few studies have used PRS to make predictions solving individuals in the overlapping periods using either ar- about the relative statures of ancient populations (29–31) but chaeological or genetic context (Methods). These groups broadly looked at only a few hundred individuals in total and did not correspond to transitions in both archaeological culture and genetic compare their predictions with stature measured from skeletons. ancestry (33, 38, 59) (SI Appendix,Fig.S1C and D and Table S1). Here, we compare measured skeletal data to genetic predictions and directly investigate the genetic contribution to height inde- Trends in PRS for Height Are Largely Consistent with Trends in pendent of environmental effects acting during development. Skeletal Stature. Both PRS and skeletal stature decreased from the EUP to Mesolithic periods and increased between the Results Neolithic and post-Neolithic (SI Appendix, Fig. S2). Fitting group PRS and Skeletal Measurements. We collected published aDNA (time period) as a covariate, we found a significant effect on − data from 1,071 ancient individuals from Western Eurasia (west of PRS(GWAS) (ANOVA P = 1.9 × 10 9), PRS(GWAS/Sibs) (P = − 50° E), dated to between 38,000 and 1100 BP (27, 29, 30, 32–57). 0.045), and skeletal stature (P = 2.8 × 10 11). There was no Using GWAS summary statistics for height from the UK Biobank evidence of difference between LUP, Mesolithic, and Neolithic (generated and made available by the Neale Laboratory: http:// groups (SI Appendix, Fig. S3 A and B), so we merged these www.nealelab.is/), we computed height PRS for each individual, 3 groups (we refer to the merged group as LUP-Neolithic). We − using a P value cutoff of 10 6, clumping