11 results on '"Moore, Kristjan H.S."'
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2. The rate and nature of mitochondrial DNA mutations in human pedigrees
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Árnadóttir, Erla R., Moore, Kristján H.S., Guðmundsdóttir, Valdís B., Ebenesersdóttir, S. Sunna, Guity, Kamran, Jónsson, Hákon, Stefánsson, Kári, and Helgason, Agnar
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- 2024
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3. The genetic history of Scandinavia from the Roman Iron Age to the present
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Rodríguez-Varela, Ricardo, Moore, Kristjan H.S., Ebenesersdóttir, S. Sunna, Kilinc, Gulsah Merve, Kjellström, Anna, Papmehl-Dufay, Ludvig, Alfsdotter, Clara, Berglund, Birgitta, Alrawi, Loey, Kashuba, Natalija, Sobrado, Verónica, Lagerholm, Vendela Kempe, Gilbert, Edmund, Cavalleri, Gianpiero L., Hovig, Eivind, Kockum, Ingrid, Olsson, Tomas, Alfredsson, Lars, Hansen, Thomas F., Werge, Thomas, Munters, Arielle R., Bernhardsson, Carolina, Skar, Birgitte, Christophersen, Axel, Turner-Walker, Gordon, Gopalakrishnan, Shyam, Daskalaki, Eva, Omrak, Ayça, Pérez-Ramallo, Patxi, Skoglund, Pontus, Girdland-Flink, Linus, Gunnarsson, Fredrik, Hedenstierna-Jonson, Charlotte, Gilbert, M. Thomas P., Lidén, Kerstin, Jakobsson, Mattias, Einarsson, Lars, Victor, Helena, Krzewińska, Maja, Zachrisson, Torun, Storå, Jan, Stefánsson, Kári, Helgason, Agnar, and Götherström, Anders
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- 2023
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4. Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura
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Bjornsdottir, Gyda, Chalmer, Mona A., Stefansdottir, Lilja, Skuladottir, Astros Th, Einarsson, Gudmundur, Andresdottir, Margret, Beyter, Doruk, Ferkingstad, Egil, Gretarsdottir, Solveig, Halldorsson, Bjarni V., Halldorsson, Gisli H., Helgadottir, Anna, Helgason, Hannes, Hjorleifsson Eldjarn, Grimur, Jonasdottir, Adalbjorg, Jonasdottir, Aslaug, Jonsdottir, Ingileif, Knowlton, Kirk U., Nadauld, Lincoln D., Lund, Sigrun H., Magnusson, Olafur Th, Melsted, Pall, Moore, Kristjan H.S., Oddsson, Asmundur, Olason, Pall I., Sigurdsson, Asgeir, Banasik, Karina, Brunak, Søren, Didriksen, Maria, Kogelman, Lisette J.A., Nielsen, Kaspar R., Sørensen, Erik, Pedersen, Ole B., Ullum, Henrik, Bay, Jakob, Burgdorf, Kristoffer, Dowsett, Joseph, Hjalgrim, Henrik, Jacobsen, Rikke L., Louloudis, Ioannis, Lundgaard, Agnete, Mikkelsen, Christina, Nyegaard, Mette, Henriksen, Alexander P., Werge, Thomas, Westergaard, David, Olesen, Jes, Ostrowski, Sisse R., Hansen, Thomas F., Bjornsdottir, Gyda, Chalmer, Mona A., Stefansdottir, Lilja, Skuladottir, Astros Th, Einarsson, Gudmundur, Andresdottir, Margret, Beyter, Doruk, Ferkingstad, Egil, Gretarsdottir, Solveig, Halldorsson, Bjarni V., Halldorsson, Gisli H., Helgadottir, Anna, Helgason, Hannes, Hjorleifsson Eldjarn, Grimur, Jonasdottir, Adalbjorg, Jonasdottir, Aslaug, Jonsdottir, Ingileif, Knowlton, Kirk U., Nadauld, Lincoln D., Lund, Sigrun H., Magnusson, Olafur Th, Melsted, Pall, Moore, Kristjan H.S., Oddsson, Asmundur, Olason, Pall I., Sigurdsson, Asgeir, Banasik, Karina, Brunak, Søren, Didriksen, Maria, Kogelman, Lisette J.A., Nielsen, Kaspar R., Sørensen, Erik, Pedersen, Ole B., Ullum, Henrik, Bay, Jakob, Burgdorf, Kristoffer, Dowsett, Joseph, Hjalgrim, Henrik, Jacobsen, Rikke L., Louloudis, Ioannis, Lundgaard, Agnete, Mikkelsen, Christina, Nyegaard, Mette, Henriksen, Alexander P., Werge, Thomas, Westergaard, David, Olesen, Jes, Ostrowski, Sisse R., and Hansen, Thomas F.
- Abstract
Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2, PALMD, ABO and LRRK2) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A, encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis-regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.
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- 2023
5. Deficit of homozygosity among 1.52 million individuals and genetic causes of recessive lethality
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Oddsson, Asmundur, Sulem, Patrick, Sveinbjornsson, Gardar, Arnadottir, Gudny A., Steinthorsdottir, Valgerdur, Halldorsson, Gisli H., Atlason, Bjarni A., Oskarsson, Gudjon R., Helgason, Hannes, Nielsen, Henriette Svarre, Westergaard, David, Karjalainen, Juha M., Katrinardottir, Hildigunnur, Fridriksdottir, Run, Jensson, Brynjar O., Tragante, Vinicius, Ferkingstad, Egil, Jonsson, Hakon, Gudjonsson, Sigurjon A., Beyter, Doruk, Moore, Kristjan H.S., Thordardottir, Helga B., Kristmundsdottir, Snaedis, Stefansson, Olafur A., Rantapää-Dahlqvist, Solbritt, Sonderby, Ida Elken, Didriksen, Maria, Stridh, Pernilla, Haavik, Jan, Tryggvadottir, Laufey, Frei, Oleksandr, Walters, G. Bragi, Kockum, Ingrid, Hjalgrim, Henrik, Olafsdottir, Thorunn A., Selbaek, Geir, Nyegaard, Mette, Erikstrup, Christian, Brodersen, Thorsten, Saevarsdottir, Saedis, Olsson, Tomas, Nielsen, Kaspar Rene, Hansen, Thomas Folkmann, Brunak, Søren, Jacobsen, Rikke Louise, Brunak, Soren, Banasik, Karina, Askling, Johan, Pedersen, Ole Birger, Ostrowski, Sisse Rye, Oddsson, Asmundur, Sulem, Patrick, Sveinbjornsson, Gardar, Arnadottir, Gudny A., Steinthorsdottir, Valgerdur, Halldorsson, Gisli H., Atlason, Bjarni A., Oskarsson, Gudjon R., Helgason, Hannes, Nielsen, Henriette Svarre, Westergaard, David, Karjalainen, Juha M., Katrinardottir, Hildigunnur, Fridriksdottir, Run, Jensson, Brynjar O., Tragante, Vinicius, Ferkingstad, Egil, Jonsson, Hakon, Gudjonsson, Sigurjon A., Beyter, Doruk, Moore, Kristjan H.S., Thordardottir, Helga B., Kristmundsdottir, Snaedis, Stefansson, Olafur A., Rantapää-Dahlqvist, Solbritt, Sonderby, Ida Elken, Didriksen, Maria, Stridh, Pernilla, Haavik, Jan, Tryggvadottir, Laufey, Frei, Oleksandr, Walters, G. Bragi, Kockum, Ingrid, Hjalgrim, Henrik, Olafsdottir, Thorunn A., Selbaek, Geir, Nyegaard, Mette, Erikstrup, Christian, Brodersen, Thorsten, Saevarsdottir, Saedis, Olsson, Tomas, Nielsen, Kaspar Rene, Hansen, Thomas Folkmann, Brunak, Søren, Jacobsen, Rikke Louise, Brunak, Soren, Banasik, Karina, Askling, Johan, Pedersen, Ole Birger, and Ostrowski, Sisse Rye
- Abstract
Genotypes causing pregnancy loss and perinatal mortality are depleted among living individuals and are therefore difficult to find. To explore genetic causes of recessive lethality, we searched for sequence variants with deficit of homozygosity among 1.52 million individuals from six European populations. In this study, we identified 25 genes harboring protein-altering sequence variants with a strong deficit of homozygosity (10% or less of predicted homozygotes). Sequence variants in 12 of the genes cause Mendelian disease under a recessive mode of inheritance, two under a dominant mode, but variants in the remaining 11 have not been reported to cause disease. Sequence variants with a strong deficit of homozygosity are over-represented among genes essential for growth of human cell lines and genes orthologous to mouse genes known to affect viability. The function of these genes gives insight into the genetics of intrauterine lethality. We also identified 1077 genes with homozygous predicted loss-of-function genotypes not previously described, bringing the total set of genes completely knocked out in humans to 4785.
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- 2023
6. Evaluation of Large-Scale Proteomics for Prediction of Cardiovascular Events
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Helgason, Hannes, Eiriksdottir, Thjodbjorg, Ulfarsson, Magnus O., Choudhary, Abhishek, Lund, Sigrun H., Ivarsdottir, Erna V., Hjorleifsson Eldjarn, Grimur, Einarsson, Gudmundur, Ferkingstad, Egil, Moore, Kristjan H.S., Honarpour, Narimon, Liu, Thomas, Wang, Huei, Hucko, Thomas, Sabatine, Marc S., Morrow, David A., Giugliano, Robert P., Ostrowski, Sisse Rye, Pedersen, Ole Birger, Bundgaard, Henning, Erikstrup, Christian, Arnar, David O., Thorgeirsson, Gudmundur, Masson, Gísli, Magnusson, Olafur Th, Saemundsdottir, Jona, Gretarsdottir, Solveig, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Helgadottir, Anna, Sulem, Patrick, Thorsteinsdottir, Unnur, Holm, Hilma, Gudbjartsson, Daniel, Stefansson, Kari, Helgason, Hannes, Eiriksdottir, Thjodbjorg, Ulfarsson, Magnus O., Choudhary, Abhishek, Lund, Sigrun H., Ivarsdottir, Erna V., Hjorleifsson Eldjarn, Grimur, Einarsson, Gudmundur, Ferkingstad, Egil, Moore, Kristjan H.S., Honarpour, Narimon, Liu, Thomas, Wang, Huei, Hucko, Thomas, Sabatine, Marc S., Morrow, David A., Giugliano, Robert P., Ostrowski, Sisse Rye, Pedersen, Ole Birger, Bundgaard, Henning, Erikstrup, Christian, Arnar, David O., Thorgeirsson, Gudmundur, Masson, Gísli, Magnusson, Olafur Th, Saemundsdottir, Jona, Gretarsdottir, Solveig, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Helgadottir, Anna, Sulem, Patrick, Thorsteinsdottir, Unnur, Holm, Hilma, Gudbjartsson, Daniel, and Stefansson, Kari
- Abstract
Importance: Whether protein risk scores derived from a single plasma sample could be useful for risk assessment for atherosclerotic cardiovascular disease (ASCVD), in conjunction with clinical risk factors and polygenic risk scores, is uncertain. Objective: To develop protein risk scores for ASCVD risk prediction and compare them to clinical risk factors and polygenic risk scores in primary and secondary event populations. Design, Setting, and Participants: The primary analysis was a retrospective study of primary events among 13540 individuals in Iceland (aged 40-75 years) with proteomics data and no history of major ASCVD events at recruitment (study duration, August 23, 2000 until October 26, 2006; follow-up through 2018). We also analyzed a secondary event population from a randomized, double-blind lipid-lowering clinical trial (2013-2016), consisting of individuals with stable ASCVD receiving statin therapy and for whom proteomic data were available for 6791 individuals. Exposures: Protein risk scores (based on 4963 plasma protein levels and developed in a training set in the primary event population); polygenic risk scores for coronary artery disease and stroke; and clinical risk factors that included age, sex, statin use, hypertension treatment, type 2 diabetes, body mass index, and smoking status at the time of plasma sampling. Main Outcomes and Measures: Outcomes were composites of myocardial infarction, stroke, and coronary heart disease death or cardiovascular death. Performance was evaluated using Cox survival models and measures of discrimination and reclassification that accounted for the competing risk of non-ASCVD death. Results: In the primary event population test set (4018 individuals [59.0% women]; 465 events; median follow-up, 15.8 years), the protein risk score had a hazard ratio (HR) of 1.93 per SD (95% CI, 1.75 to 2.13). Addition of protein risk score and polygenic risk scores significantly increased the C index when added to a clinical ri
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- 2023
7. The population genomic legacy of the second plague pandemic
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Gopalakrishnan, Shyam, primary, Ebenesersdóttir, S. Sunna, additional, Lundstrøm, Inge K.C., additional, Turner-Walker, Gordon, additional, Moore, Kristjan H.S., additional, Luisi, Pierre, additional, Margaryan, Ashot, additional, Martin, Michael D., additional, Ellegaard, Martin Rene, additional, Magnússon, Ólafur þ., additional, Sigurðsson, Ásgeir, additional, Snorradóttir, Steinunn, additional, Magnúsdóttir, Droplaug N., additional, Laffoon, Jason E., additional, van Dorp, Lucy, additional, Liu, Xiaodong, additional, Moltke, Ida, additional, Ávila-Arcos, María C., additional, Schraiber, Joshua G., additional, Rasmussen, Simon, additional, Juan, David, additional, Gelabert, Pere, additional, de-Dios, Toni, additional, Fotakis, Anna K., additional, Iraeta-Orbegozo, Miren, additional, Vågene, Åshild J., additional, Denham, Sean Dexter, additional, Christophersen, Axel, additional, Stenøien, Hans K., additional, Vieira, Filipe G., additional, Liu, Shanlin, additional, Günther, Torsten, additional, Kivisild, Toomas, additional, Moseng, Ole Georg, additional, Skar, Birgitte, additional, Cheung, Christina, additional, Sandoval-Velasco, Marcela, additional, Wales, Nathan, additional, Schroeder, Hannes, additional, Campos, Paula F., additional, Guðmundsdóttir, Valdís B., additional, Sicheritz-Ponten, Thomas, additional, Petersen, Bent, additional, Halgunset, Jostein, additional, Gilbert, Edmund, additional, Cavalleri, Gianpiero L., additional, Hovig, Eivind, additional, Kockum, Ingrid, additional, Olsson, Tomas, additional, Alfredsson, Lars, additional, Hansen, Thomas F., additional, Werge, Thomas, additional, Willerslev, Eske, additional, Balloux, Francois, additional, Marques-Bonet, Tomas, additional, Lalueza-Fox, Carles, additional, Nielsen, Rasmus, additional, Stefánsson, Kári, additional, Helgason, Agnar, additional, and Gilbert, M. Thomas P., additional
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- 2022
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8. Multiomics analysis of rheumatoid arthritis yields sequence variants that have large effects on risk of the seropositive subset
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Saevarsdottir, Saedis, Stefansdottir, Lilja, Sulem, Patrick, Thorleifsson, Gudmar, Ferkingstad, Egil, Rutsdottir, Gudrun, Glintborg, Bente, Westerlind, Helga, Grondal, Gerdur, Loft, Isabella C., Sorensen, Signe Bek, Lie, Benedicte A., Brink, Mikael, Ärlestig, Lisbeth, Arnthorsson, Asgeir Orn, Baecklund, Eva, Banasik, Karina, Bank, Steffen, Bjorkman, Lena I., Ellingsen, Torkell, Erikstrup, Christian, Frei, Oleksandr, Gjertsson, Inger, Gudbjartsson, Daniel F., Gudjonsson, Sigurjon A., Halldorsson, Gisli H., Hendricks, Oliver, Hillert, Jan, Hogdall, Estrid, Jacobsen, Søren, Jensen, Dorte Vendelbo, Jonsson, Helgi, Kastbom, Alf, Kockum, Ingrid, Kristensen, Salome, Kristjansdottir, Helga, Larsen, Margit H., Linauskas, Asta, Hauge, Ellen-Margrethe, Loft, Anne G., Ludviksson, Bjorn R., Lund, Sigrun H., Markusson, Thorsteinn, Masson, Gisli, Melsted, Pall, Moore, Kristjan H.S., Munk, Heidi, Nielsen, Kaspar R., Norddahl, Gudmundur L., Oddsson, Asmundur, Olafsdottir, Thorunn A., Olason, Pall I., Olsson, Tomas, Ostrowski, Sisse Rye, Hørslev-Petersen, Kim, Rognvaldsson, Solvi, Sanner, Helga, Silberberg, Gilad N., Stefansson, Hreinn, Sørensen, Erik, Sørensen, Inge J., Turesson, Carl, Bergman, Thomas, Alfredsson, Lars, Kvien, Tore K., Brunak, Søren, Steinsson, Kristján, Andersen, Vibeke, Andreassen, Ole A., Rantapää-Dahlqvist, Solbritt, Hetland, Merete Lund, Klareskog, Lars, Askling, Johan, Padyukov, Leonid, Pedersen, Ole Bv, Thorsteinsdottir, Unnur, Jonsdottir, Ingileif, Stefansson, Kari, Saevarsdottir, Saedis, Stefansdottir, Lilja, Sulem, Patrick, Thorleifsson, Gudmar, Ferkingstad, Egil, Rutsdottir, Gudrun, Glintborg, Bente, Westerlind, Helga, Grondal, Gerdur, Loft, Isabella C., Sorensen, Signe Bek, Lie, Benedicte A., Brink, Mikael, Ärlestig, Lisbeth, Arnthorsson, Asgeir Orn, Baecklund, Eva, Banasik, Karina, Bank, Steffen, Bjorkman, Lena I., Ellingsen, Torkell, Erikstrup, Christian, Frei, Oleksandr, Gjertsson, Inger, Gudbjartsson, Daniel F., Gudjonsson, Sigurjon A., Halldorsson, Gisli H., Hendricks, Oliver, Hillert, Jan, Hogdall, Estrid, Jacobsen, Søren, Jensen, Dorte Vendelbo, Jonsson, Helgi, Kastbom, Alf, Kockum, Ingrid, Kristensen, Salome, Kristjansdottir, Helga, Larsen, Margit H., Linauskas, Asta, Hauge, Ellen-Margrethe, Loft, Anne G., Ludviksson, Bjorn R., Lund, Sigrun H., Markusson, Thorsteinn, Masson, Gisli, Melsted, Pall, Moore, Kristjan H.S., Munk, Heidi, Nielsen, Kaspar R., Norddahl, Gudmundur L., Oddsson, Asmundur, Olafsdottir, Thorunn A., Olason, Pall I., Olsson, Tomas, Ostrowski, Sisse Rye, Hørslev-Petersen, Kim, Rognvaldsson, Solvi, Sanner, Helga, Silberberg, Gilad N., Stefansson, Hreinn, Sørensen, Erik, Sørensen, Inge J., Turesson, Carl, Bergman, Thomas, Alfredsson, Lars, Kvien, Tore K., Brunak, Søren, Steinsson, Kristján, Andersen, Vibeke, Andreassen, Ole A., Rantapää-Dahlqvist, Solbritt, Hetland, Merete Lund, Klareskog, Lars, Askling, Johan, Padyukov, Leonid, Pedersen, Ole Bv, Thorsteinsdottir, Unnur, Jonsdottir, Ingileif, and Stefansson, Kari
- Abstract
Objectives: To find causal genes for rheumatoid arthritis (RA) and its seropositive (RF and/or ACPA positive) and seronegative subsets. Methods: We performed a genome-wide association study (GWAS) of 31 313 RA cases (68% seropositive) and ∼1 million controls from Northwestern Europe. We searched for causal genes outside the HLA-locus through effect on coding, mRNA expression in several tissues and/or levels of plasma proteins (SomaScan) and did network analysis (Qiagen). Results: We found 25 sequence variants for RA overall, 33 for seropositive and 2 for seronegative RA, altogether 37 sequence variants at 34 non-HLA loci, of which 15 are novel. Genomic, transcriptomic and proteomic analysis of these yielded 25 causal genes in seropositive RA and additional two overall. Most encode proteins in the network of interferon-Alpha/beta and IL-12/23 that signal through the JAK/STAT-pathway. Highlighting those with largest effect on seropositive RA, a rare missense variant in STAT4 (rs140675301-A) that is independent of reported non-coding STAT4-variants, increases the risk of seropositive RA 2.27-fold (p=2.1×10-9), more than the rs2476601-A missense variant in PTPN22 (OR=1.59, p=1.3×10-160). STAT4 rs140675301-A replaces hydrophilic glutamic acid with hydrophobic valine (Glu128Val) in a conserved, surface-exposed loop. A stop-mutation (rs76428106-C) in FLT3 increases seropositive RA risk (OR=1.35, p=6.6×10-11). Independent missense variants in TYK2 (rs34536443-C, rs12720356-C, rs35018800-A, latter two novel) associate with decreased risk of seropositive RA (ORs=0.63-0.87, p=10-9-10-27) and decreased plasma levels of interferon-Alpha/beta receptor 1 that signals through TYK2/JAK1/STAT4. Conclusion: Sequence variants pointing to causal genes in the JAK/STAT pathway have largest effect on seropositive RA, while associations with seronegative RA remain scarce.
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- 2022
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9. The population genomic legacy of the second plague pandemic
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Carlsberg Foundation, Danish National Research Foundation, Lundbeck Foundation, European Research Council, Research Council of Norway, Science Foundation Ireland, Gopalakrishnan, Shyam, Ebenesersdóttir, Sigríður Sunna, Lundstrøm, Inge K.C., Turner-Walker, Gordon, Moore, Kristjan H.S., Luisi, Pierre, Margaryan, Ashot, Martin, Michael D., Ellegaard, Martin Rene, Magnusson, Olafur þ., Sigurðsson, Ásgeir, Snorradóttir, Steinunn, Magnúsdóttir, Droplaug N., Laffoon, Jason, van Dorp, Lucy, Liu, Xiaodong, Moltke, Ida, Ávila-Arcos, María C., Schraiber, Joshua G., Rasmussen,Simon, Juan, David, Gelabert, Pere, De-Dios, Toni, Fotakis, Anna K., Iraeta-Orbegozo, Miren, Vågene, Åshild J., Dexter Denham, Sean, Christophersen, Axel, Stenøien, Hans K., Vieira, Filipe Garrett, Liu, Shanlin, Günther, Torsten, Kivisild, Toomas, Moseng, Ole Georg, Skar, Birgitte, Cheung, Christina, Sandoval-Velasco, Marcela, Wales, Nathan, Schroeder, Hannes, Campos, Paula F., Guðmundsdóttir, Valdís B., Sicheritz-Ponten, Thomas, Petersen, Bent, Halgunset, Jostein, Gilbert, Edmund, Cavalleri, Gianpiero L., Hovig, Eivind, Kockum, Ingrid, Olsson, Tomas, Alfredsson, Lars, Hansen, Thomas F., Werge, Thomas, Willerslev, Eske, Balloux, François, Marqués-Bonet, Tomàs, Lalueza-Fox, Carles, Nielsen, Rasmus, Stefánsson, Kári, Helgason, Agnar, Gilbert, M. Thomas P., Carlsberg Foundation, Danish National Research Foundation, Lundbeck Foundation, European Research Council, Research Council of Norway, Science Foundation Ireland, Gopalakrishnan, Shyam, Ebenesersdóttir, Sigríður Sunna, Lundstrøm, Inge K.C., Turner-Walker, Gordon, Moore, Kristjan H.S., Luisi, Pierre, Margaryan, Ashot, Martin, Michael D., Ellegaard, Martin Rene, Magnusson, Olafur þ., Sigurðsson, Ásgeir, Snorradóttir, Steinunn, Magnúsdóttir, Droplaug N., Laffoon, Jason, van Dorp, Lucy, Liu, Xiaodong, Moltke, Ida, Ávila-Arcos, María C., Schraiber, Joshua G., Rasmussen,Simon, Juan, David, Gelabert, Pere, De-Dios, Toni, Fotakis, Anna K., Iraeta-Orbegozo, Miren, Vågene, Åshild J., Dexter Denham, Sean, Christophersen, Axel, Stenøien, Hans K., Vieira, Filipe Garrett, Liu, Shanlin, Günther, Torsten, Kivisild, Toomas, Moseng, Ole Georg, Skar, Birgitte, Cheung, Christina, Sandoval-Velasco, Marcela, Wales, Nathan, Schroeder, Hannes, Campos, Paula F., Guðmundsdóttir, Valdís B., Sicheritz-Ponten, Thomas, Petersen, Bent, Halgunset, Jostein, Gilbert, Edmund, Cavalleri, Gianpiero L., Hovig, Eivind, Kockum, Ingrid, Olsson, Tomas, Alfredsson, Lars, Hansen, Thomas F., Werge, Thomas, Willerslev, Eske, Balloux, François, Marqués-Bonet, Tomàs, Lalueza-Fox, Carles, Nielsen, Rasmus, Stefánsson, Kári, Helgason, Agnar, and Gilbert, M. Thomas P.
- Abstract
Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.
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- 2022
10. The sequences of 150,119 genomes in the UK Biobank
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Halldorsson, Bjarni V., Eggertsson, Hannes P., Moore, Kristjan H.S., Hauswedell, Hannes, Eiriksson, Ogmundur, Ulfarsson, Magnus O., Palsson, Gunnar, Hardarson, Marteinn T., Oddsson, Asmundur, Jensson, Brynjar O., Kristmundsdottir, Snaedis, Sigurpalsdottir, Brynja D., Stefansson, Olafur A., Beyter, Doruk, Holley, Guillaume, Tragante, Vinicius, Gylfason, Arnaldur, Olason, Pall I., Zink, Florian, Asgeirsdottir, Margret, Sverrisson, Sverrir T., Sigurdsson, Brynjar, Gudjonsson, Sigurjon A., Sigurdsson, Gunnar T., Halldorsson, Gisli H., Sveinbjornsson, Gardar, Norland, Kristjan, Styrkarsdottir, Unnur, Magnusdottir, Droplaug N., Snorradottir, Steinunn, Kristinsson, Kari, Sobech, Emilia, Pedersen, Ole Birger, Brunak, Søren, Ostrowski, Sisse Rye, Banasik, Karina, Burgdorf, Kristoffer, Didriksen, Maria, Hansen, Thomas Folkmann, Hjalgrim, Henrik, Jemec, Gregor, Jennum, Poul, Johansson, Pär Ingemar, Ullum, Henrik, Werge, Thomas, Halldorsson, Bjarni V., Eggertsson, Hannes P., Moore, Kristjan H.S., Hauswedell, Hannes, Eiriksson, Ogmundur, Ulfarsson, Magnus O., Palsson, Gunnar, Hardarson, Marteinn T., Oddsson, Asmundur, Jensson, Brynjar O., Kristmundsdottir, Snaedis, Sigurpalsdottir, Brynja D., Stefansson, Olafur A., Beyter, Doruk, Holley, Guillaume, Tragante, Vinicius, Gylfason, Arnaldur, Olason, Pall I., Zink, Florian, Asgeirsdottir, Margret, Sverrisson, Sverrir T., Sigurdsson, Brynjar, Gudjonsson, Sigurjon A., Sigurdsson, Gunnar T., Halldorsson, Gisli H., Sveinbjornsson, Gardar, Norland, Kristjan, Styrkarsdottir, Unnur, Magnusdottir, Droplaug N., Snorradottir, Steinunn, Kristinsson, Kari, Sobech, Emilia, Pedersen, Ole Birger, Brunak, Søren, Ostrowski, Sisse Rye, Banasik, Karina, Burgdorf, Kristoffer, Didriksen, Maria, Hansen, Thomas Folkmann, Hjalgrim, Henrik, Jemec, Gregor, Jennum, Poul, Johansson, Pär Ingemar, Ullum, Henrik, and Werge, Thomas
- Abstract
Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank3. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.
- Published
- 2022
11. The genetic structure of Norway
- Author
-
Mattingsdal, Morten, Ebenesersdóttir, S. Sunna, Moore, Kristjan H.S., Andreassen, Ole A., Hansen, Thomas F., Werge, Thomas, Kockum, Ingrid, Olsson, Tomas, Alfredsson, Lars, Helgason, Agnar, Stefánsson, Kári, Hovig, Eivind, Mattingsdal, Morten, Ebenesersdóttir, S. Sunna, Moore, Kristjan H.S., Andreassen, Ole A., Hansen, Thomas F., Werge, Thomas, Kockum, Ingrid, Olsson, Tomas, Alfredsson, Lars, Helgason, Agnar, Stefánsson, Kári, and Hovig, Eivind
- Abstract
The aim of the present study was to describe the genetic structure of the Norwegian population using genotypes from 6369 unrelated individuals with detailed information about places of residence. Using standard single marker- and haplotype-based approaches, we report evidence of two regions with distinctive patterns of genetic variation, one in the far northeast, and another in the south of Norway, as indicated by fixation indices, haplotype sharing, homozygosity, and effective population size. We detect and quantify a component of Uralic Sami ancestry that is enriched in the North. On a finer scale, we find that rates of migration have been affected by topography like mountain ridges. In the broader Scandinavian context, we detect elevated relatedness between the mid- and northern border areas towards Sweden. The main finding of this study is that despite Norway’s long maritime history and as a former Danish territory, the region closest to mainland Europe in the south appears to have been an isolated region in Norway, highlighting the open sea as a barrier to gene flow into Norway.
- Published
- 2021
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