Nationwide Genomic Study in Denmark Reveals Remarkable Population Homogeneity

Abstract

Denmark has played a substantial role in the history of Northern Europe. Through a nationwide scientific outreach initiative, we collected genetic and anthropometrical data from ∼800 high school students and used them to elucidate the genetic makeup of the Danish population, as well as to assess polygenic predictions of phenotypic traits in adolescents. We observed remarkable homogeneity across different geographic regions, although we could still detect weak signals of genetic structure reflecting the history of the country. Denmark presented genomic affinity with primarily neighboring countries with overall resemblance of decreasing weight from Britain, Sweden, Norway, Germany, and France. A Polish admixture signal was detected in Zealand and Funen, and our date estimates coincided with historical evidence of Wend settlements in the south of Denmark. We also observed considerably diverse demographic histories among Scandinavian countries, with Denmark having the smallest current effective population size compared to Norway and Sweden. Finally, we found that polygenic prediction of self-reported adolescent height in the population was remarkably accurate (R² = 0.639 ± 0.015). The high homogeneity of the Danish population could render population structure a lesser concern for the upcoming large-scale gene-mapping studies in the country.

Keywords: admixture; genetic prediction; human population genetics; polygenic risk score; population structure.

Figure 1

Location of the 36 Danish high schools participating in the Where Are You From? project colored by geographic origin. Number of samples with at least three grandparents born in each of the six regions is shown in parentheses.

Figure 2

(A) PCA of 105,672 imputed SNPs after merging four data sets: Where Are You From?, POPRES, NCNG, and the Swedish Schizophrenia Study without outliers clustering with Finland (total N = 3858). Per-country box plots (median and interquartile range) of PC values were added to facilitate interpretation. Whiskers represent data within 1.5 times the interquartile range. IE: Ireland; ES: Spain; PT: Portugal; GB: Great Britain; FR: France; BE: Belgium; CH: Switzerland; NL: the Netherlands; DK: Denmark; DE: Germany; NO: Norway; SE: Sweden; AT: Austria; IT: Italy; PL: Poland; HU: Hungary; CZ: Czech Republic; HR: Croatia; RO: Romania; YU: Yugoslavia; GR: Greece. (B) PCA of 105,672 imputed SNPs from Denmark, Sweden, Norway and Germany with emphasis on the six geographic regions of Denmark (total N = 1168). No clear genetic–geographic relationship was observed. Ca: Capital; Ze: Zealand; Fu: Funen; SJ: South Jutland; CJ: Central Jutland; NJ: North Jutland. (C) Correlation of PC1 and PC2 with average grandparent place-of-birth latitude along a 360° Clockwise rotation. Maximum correlation was observed for PC1 at 32° (r ≈ 0.24; P < 10⁻⁵).

Figure 3

(A) fineSTRUCTURE grouping of the 2745 European donor samples into eight clusters roughly corresponding to well-defined geographic locations. The tree on the left illustrates cluster topology. Pie charts on the European map show the relative contribution from each country to each of the eight inferred clusters. FIN: Finnish; NOR: Norwegian; SWE: Swedish; POL: Polish; GER: German; BRI: British; FRA: French; IBE: Iberian. Color legend at the bottom of the map shows different donor countries. FI: Finland. (B) GLOBETROTTER admixture proportions of each of the eight European clusters in the six geographic regions of Denmark. Neither FIN nor IBE made substantial contributions (<2.5%) to the mixture profiles of Denmark.

Figure 4

Ancestral component analysis of 13 European countries (including six well-defined geographic regions in Denmark shown in the inset) assuming K = 4 ancestral populations. Bar plot at the bottom shows per-individual membership to each of the four ancestral components, whereas pie charts on the map resume per-country (or per-region for Denmark) admixture proportions. Based on their preponderance in different parts of Europe, we interpret the four components as (i) Southern European (blue); (ii) Eastern European (yellow); (iii) Nordic (green); and (iv) Central European (red). Regions from south and east Denmark show higher proportion of Eastern European ancestry in accord with Figure 3B and Table S2.

Figure 5

(A) Distribution of geographic distance of each participant’s place of birth (N = 399) to that of their closest “genomic relative” (pink) and to that of a randomly chosen sample (green). Genomic relatedness was defined on the grounds of total genomic IBD. Arrows point at median values of the two distributions (median_rltv = 99.3 km; median_rand = 131.4 km). Seven individuals with unknown geographic coordinates were excluded from this analysis. (B) Plot of rank of genomic relatedness vs. median geographic distance of each participant to their closest genomic relative. We created 57 equally sized bins of individuals increasingly related to their closest genomic relative (seven individuals per bin). Alternative bin sizes also produced significantly negative correlations (data not shown).

Figure 6

Change in effective population size (N_e) of the Danish, Swedish, and Norwegian populations over the past 150 generations (log scale). Shaded areas represent the upper and lower bounds of the 95% confidence intervals after bootstrapping. Uncertainty in generation length is represented by year intervals on the x-axis, assuming that each generation lasts 30 ± 2 years. Black segments represent major epidemics from the recent history of the Danish population and are plotted taking into account generation length uncertainty. For more clarity, the inset shows the same graph with both axes in log scale.