Genetic architecture in Greenland is shaped by demography, structure and selection
Frederik Filip Stæger, Mette K. Andersen, Zilong Li, Jasmin Pernille Hjerresen, Shixu He, Cindy G. Santander, Rasmus Tanderup Jensen, Karsten Fleischer Rex, Anne Cathrine B. Thuesen, Kristian Hanghøj, Inge Høst Seiding, Emil Jørsboe, Sara Stinson, Malthe Sebro Rasmussen, Renzo F. Balboa, Christina Viskum Lytken Larsen, Peter Bjerregaard, Mikkel Schubert, Jonas Meisner, Allan Linneberg, Niels Grarup, Eleftheria Zeggini, Rasmus Nielsen, Marit E. Jørgensen, Torben Hansen, Ida Moltke, Anders Albrechtsen
Abstract
, leading to inequity in healthcare opportunities. To address this, we performed analyses of sequenced or imputed genomes of 5,996 Greenlanders with extensive phenotypes. We quantified their historical population bottleneck and how it has shaped their genetic architecture to have fewer, but more common, variable sites. Consequently, we find twice as many high-impact genome-wide associations to metabolic traits in Greenland compared with Europe. We infer that the high-impact variants arose after the population split from Native Americans and thus are Arctic-specific, and show that some of them are common due to not only genetic drift but also selection. We also find that European-derived polygenic scores for metabolic traits are only half as accurate in Greenlanders as in Europeans, and that adding Arctic-specific variants improves the overall accuracy to the same level as in Europeans. Similarly, lack of representation in public genetic databases makes genetic clinical screening harder in Greenlandic Inuit, but inclusion of Greenlandic data remedies this by reducing the number of non-causal candidate variants by sixfold. Finally, we identify pronounced genetic fine structure that explains differences in prevalence of monogenic diseases in Greenland and, together with recent changes in mobility, leads to a predicted future reduction in risk for certain recessive diseases. These results illustrate how including data from Greenlanders can greatly reduce inequity in genomic-based healthcare.