Author
Listed:
- Frederik Filip Stæger
(Section for Computational and RNA Biology, University of Copenhagen)
- Mette K. Andersen
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Zilong Li
(Section for Computational and RNA Biology, University of Copenhagen)
- Jasmin Pernille Hjerresen
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Shixu He
(Section for Computational and RNA Biology, University of Copenhagen)
- Cindy G. Santander
(Section for Computational and RNA Biology, University of Copenhagen)
- Rasmus Tanderup Jensen
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Karsten Fleischer Rex
(Queen Ingrid’s Hospital
Arctic Health Research Centre, Aalborg University Hospital)
- Anne Cathrine Baun Thuesen
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Kristian Hanghøj
(Section for Computational and RNA Biology, University of Copenhagen)
- Inge Høst Seiding
(Ilisimatusarfik - University of Greenland)
- Emil Jørsboe
(Faculty of Health and Medical Sciences, University of Copenhagen
Big Data Institute, University of Oxford
University of Oxford)
- Sara Elizabeth Stinson
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Malthe Sebro Rasmussen
(Section for Computational and RNA Biology, University of Copenhagen)
- Renzo F. Balboa
(Section for Computational and RNA Biology, University of Copenhagen)
- Christina Viskum Lytken Larsen
(National Institute of Public Health, University of Southern Denmark
Institute for Health and Nature, University of Greenland)
- Peter Bjerregaard
(National Institute of Public Health, University of Southern Denmark)
- Mikkel Schubert
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Jonas Meisner
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Allan Linneberg
(Bispebjerg and Frederiksberg Hospital, The Capital Region of Denmark
Faculty of Health and Medical Sciences, University of Copenhagen)
- Niels Grarup
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Eleftheria Zeggini
(Helmholtz Zentrum München – German Research Center for Environmental Health
Technical University of Munich (TUM) and Klinikum Rechts der Isar)
- Rasmus Nielsen
(University of California at Berkeley
Globe Institute, University of Copenhagen)
- Marit E. Jørgensen
(National Institute of Public Health, University of Southern Denmark
Institute for Health and Nature, University of Greenland
Steno Diabetes Center Greenland)
- Torben Hansen
(Faculty of Health and Medical Sciences, University of Copenhagen)
- Ida Moltke
(Section for Computational and RNA Biology, University of Copenhagen)
- Anders Albrechtsen
(Section for Computational and RNA Biology, University of Copenhagen)
Abstract
Greenlandic Inuit and other indigenous populations are underrepresented in genetic research1,2, 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.
Suggested Citation
Frederik Filip Stæger & Mette K. Andersen & Zilong Li & Jasmin Pernille Hjerresen & Shixu He & Cindy G. Santander & Rasmus Tanderup Jensen & Karsten Fleischer Rex & Anne Cathrine Baun Thuesen & Kristi, 2025.
"Genetic architecture in Greenland is shaped by demography, structure and selection,"
Nature, Nature, vol. 639(8054), pages 404-410, March.
Handle:
RePEc:nat:nature:v:639:y:2025:i:8054:d:10.1038_s41586-024-08516-4
DOI: 10.1038/s41586-024-08516-4
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