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3 results on '"Pedersen, Anders Gorm"'

1. Early Divergent Strains of Yersinia pestis in Eurasia 5,000 Years Ago

Author

Rasmussen, Simon, Allentoft, Morten Erik, Nielsen, Kasper, Orlando, Ludovic, Sikora, Martin, Sjögren, Karl-Göran, Pedersen, Anders Gorm, Schubert, Mikkel, Van Dam, Alex, Kapel, Christian Moliin Outzen, Nielsen, Henrik Bjørn, Brunak, Søren, Avetisyan, Pavel, Epimakhov, Andrey, Khalyapin, Mikhail Viktorovich, Gnuni, Artak, Kriiska, Aivar, Lasak, Irena, Metspalu, Mait, Moiseyev, Vyacheslav, Gromov, Andrei, Pokutta, Dalia, Saag, Lehti, Varul, Liivi, Yepiskoposyan, Levon, Sicheritz-Pontén, Thomas, Foley, Robert A, Lahr, Marta Mirazón, Nielsen, Rasmus, Kristiansen, Kristian, and Willerslev, Eske

Subjects
Biological Sciences, Genetics, Biodefense, Vaccine Related, Prevention, Infectious Diseases, Emerging Infectious Diseases, Vector-Borne Diseases, Aetiology, 2.2 Factors relating to the physical environment, Infection, Animals, Asia, DNA, Bacterial, Europe, History, Ancient, History, Medieval, Humans, Plague, Siphonaptera, Tooth, Yersinia pestis, Medical and Health Sciences, Developmental Biology, Biological sciences, Biomedical and clinical sciences
Abstract

The bacteria Yersinia pestis is the etiological agent of plague and has caused human pandemics with millions of deaths in historic times. How and when it originated remains contentious. Here, we report the oldest direct evidence of Yersinia pestis identified by ancient DNA in human teeth from Asia and Europe dating from 2,800 to 5,000 years ago. By sequencing the genomes, we find that these ancient plague strains are basal to all known Yersinia pestis. We find the origins of the Yersinia pestis lineage to be at least two times older than previous estimates. We also identify a temporal sequence of genetic changes that lead to increased virulence and the emergence of the bubonic plague. Our results show that plague infection was endemic in the human populations of Eurasia at least 3,000 years before any historical recordings of pandemics.

Published
2015

2. Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models

Author

Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Leal Rodríguez, Cristina, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B, De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T, 't Hart, Leen M, Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N, Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W, Schwenk, Jochen M, Adamski, Jerzy, McCarthy, Mark I, Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, Brunak, Søren, IMI DIRECT Consortium, Lundgaard, Agnete Troen [0000-0001-7447-6560], Hernández Medina, Ricardo [0000-0001-6373-2362], Johansen, Joachim [0000-0001-7052-1870], Niu, Lili [0000-0003-4571-4368], Biel, Jorge Hernansanz [0000-0002-3125-2951], Leal Rodríguez, Cristina [0000-0002-3133-0630], Benros, Michael Eriksen [0000-0003-4939-9465], Pedersen, Anders Gorm [0000-0001-9650-8965], Jacobsen, Ulrik Plesner [0000-0001-9181-6854], Koivula, Robert [0000-0002-1646-4163], Vinuela, Ana [0000-0003-3771-8537], Haid, Mark [0000-0001-6118-1333], Hong, Mun-Gwan [0000-0001-8603-8293], Kennedy, Gwen [0000-0002-9856-3236], Thomas, E Louise [0000-0003-4235-4694], Frost, Gary [0000-0003-0529-6325], Hansen, Tue Haldor [0000-0001-5948-8993], Kaye, Jane [0000-0002-7311-4725], Hattersley, Andrew [0000-0001-5620-473X], Ridderstråle, Martin [0000-0002-3270-9167], Pedersen, Oluf [0000-0002-3321-3972], Hansen, Torben [0000-0001-8748-3831], Schwenk, Jochen M [0000-0001-8141-8449], Rasmussen, Simon [0000-0001-6323-9041], Brunak, Søren [0000-0003-0316-5866], and Apollo - University of Cambridge Repository

Subjects
Deep Learning, Diabetes Mellitus, Type 2, Humans, Algorithms
Abstract

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

Published
2023

3. Early divergent strains of Yersinia pestis in Eurasia 5,000 years ago

Author

Rasmussen, Simon, Allentoft, Morten Erik, Nielsen, Kasper, Orlando, Ludovic, Sikora, Martin, Sjögren, Karl-Göran, Pedersen, Anders Gorm, Schubert, Mikkel, Van Dam, Alex, Kapel, Christian Moliin Outzen, Nielsen, Henrik Bjørn, Brunak, Søren, Avetisyan, Pavel, Epimakhov, Andrey, Khalyapin, Mikhail Viktorovich, Gnuni, Artak, Kriiska, Aivar, Lasak, Irena, Metspalu, Mait, Moiseyev, Vyacheslav, Gromov, Andrei, Pokutta, Dalia, Saag, Lehti, Varul, Liivi, Yepiskoposyan, Levon, Sicheritz-Pontén, Thomas, Foley, Robert A, Lahr, Marta Mirazón, Nielsen, Rasmus, Kristiansen, Kristian, and Willerslev, Eske

Subjects
DNA, Bacterial, Europe, Plague, Asia, Yersinia pestis, Animals, Humans, Siphonaptera, Tooth, History, Ancient, History, Medieval, 3. Good health
Abstract

The bacteria Yersinia pestis is the etiological agent of plague and has caused human pandemics with millions of deaths in historic times. How and when it originated remains contentious. Here, we report the oldest direct evidence of Yersinia pestis identified by ancient DNA in human teeth from Asia and Europe dating from 2,800 to 5,000 years ago. By sequencing the genomes, we find that these ancient plague strains are basal to all known Yersinia pestis. We find the origins of the Yersinia pestis lineage to be at least two times older than previous estimates. We also identify a temporal sequence of genetic changes that lead to increased virulence and the emergence of the bubonic plague. Our results show that plague infection was endemic in the human populations of Eurasia at least 3,000 years before any historical recordings of pandemics.

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