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Human Disease Variation in the Light of Population Genomics

Publikation: Bidrag til tidsskriftReviewForskningpeer review

Harvard

Prohaska, A, Racimo, F, Schork, AJ, Sikora, M, Stern, AJ, Ilardo, M, Allentoft, ME, Folkersen, L, Buil, A, Moreno-Mayar, JV, Korneliussen, T, Geschwind, D, Ingason, A, Werge, T, Nielsen, R & Willerslev, E 2019, 'Human Disease Variation in the Light of Population Genomics' Cell, bind 177, nr. 1, s. 115-131. https://doi.org/10.1016/j.cell.2019.01.052

APA

Prohaska, A., Racimo, F., Schork, A. J., Sikora, M., Stern, A. J., Ilardo, M., ... Willerslev, E. (2019). Human Disease Variation in the Light of Population Genomics. Cell, 177(1), 115-131. https://doi.org/10.1016/j.cell.2019.01.052

CBE

Prohaska A, Racimo F, Schork AJ, Sikora M, Stern AJ, Ilardo M, Allentoft ME, Folkersen L, Buil A, Moreno-Mayar JV, Korneliussen T, Geschwind D, Ingason A, Werge T, Nielsen R, Willerslev E. 2019. Human Disease Variation in the Light of Population Genomics. Cell. 177(1):115-131. https://doi.org/10.1016/j.cell.2019.01.052

MLA

Vancouver

Prohaska A, Racimo F, Schork AJ, Sikora M, Stern AJ, Ilardo M o.a. Human Disease Variation in the Light of Population Genomics. Cell. 2019 mar 21;177(1):115-131. https://doi.org/10.1016/j.cell.2019.01.052

Author

Prohaska, Ana ; Racimo, Fernando ; Schork, Andrew J ; Sikora, Martin ; Stern, Aaron J ; Ilardo, Melissa ; Allentoft, Morten Erik ; Folkersen, Lasse ; Buil, Alfonso ; Moreno-Mayar, J Víctor ; Korneliussen, Thorfinn ; Geschwind, Daniel ; Ingason, Andrés ; Werge, Thomas ; Nielsen, Rasmus ; Willerslev, Eske. / Human Disease Variation in the Light of Population Genomics. I: Cell. 2019 ; Bind 177, Nr. 1. s. 115-131.

Bibtex

@article{cc1e2cefd9f440c3940fed7f030ed29a,
title = "Human Disease Variation in the Light of Population Genomics",
abstract = "Identifying the causes of similarities and differences in genetic disease prevalence among humans is central to understanding disease etiology. While present-day humans are not strongly differentiated, vast amounts of genomic data now make it possible to study subtle patterns of genetic variation. This allows us to trace our genomic history thousands of years into the past and its implications for the distribution of disease-associated variants today. Genomic analyses have shown that demographic processes shaped the distribution and frequency of disease-associated variants over time. Furthermore, local adaptation to new environmental conditions-including pathogens-has generated strong patterns of differentiation at particular loci. Researchers are also beginning to uncover the genetic architecture of complex diseases, affected by many variants of small effect. The field of population genomics thus holds great potential for providing further insights into the evolution of human disease.",
author = "Ana Prohaska and Fernando Racimo and Schork, {Andrew J} and Martin Sikora and Stern, {Aaron J} and Melissa Ilardo and Allentoft, {Morten Erik} and Lasse Folkersen and Alfonso Buil and Moreno-Mayar, {J V{\'i}ctor} and Thorfinn Korneliussen and Daniel Geschwind and Andr{\'e}s Ingason and Thomas Werge and Rasmus Nielsen and Eske Willerslev",
note = "Copyright {\circledC} 2019 Elsevier Inc. All rights reserved.",
year = "2019",
month = "3",
day = "21",
doi = "10.1016/j.cell.2019.01.052",
language = "English",
volume = "177",
pages = "115--131",
journal = "Cell",
issn = "0092-8674",
publisher = "Cell Press",
number = "1",

}

RIS

TY - JOUR

T1 - Human Disease Variation in the Light of Population Genomics

AU - Prohaska, Ana

AU - Racimo, Fernando

AU - Schork, Andrew J

AU - Sikora, Martin

AU - Stern, Aaron J

AU - Ilardo, Melissa

AU - Allentoft, Morten Erik

AU - Folkersen, Lasse

AU - Buil, Alfonso

AU - Moreno-Mayar, J Víctor

AU - Korneliussen, Thorfinn

AU - Geschwind, Daniel

AU - Ingason, Andrés

AU - Werge, Thomas

AU - Nielsen, Rasmus

AU - Willerslev, Eske

N1 - Copyright © 2019 Elsevier Inc. All rights reserved.

PY - 2019/3/21

Y1 - 2019/3/21

N2 - Identifying the causes of similarities and differences in genetic disease prevalence among humans is central to understanding disease etiology. While present-day humans are not strongly differentiated, vast amounts of genomic data now make it possible to study subtle patterns of genetic variation. This allows us to trace our genomic history thousands of years into the past and its implications for the distribution of disease-associated variants today. Genomic analyses have shown that demographic processes shaped the distribution and frequency of disease-associated variants over time. Furthermore, local adaptation to new environmental conditions-including pathogens-has generated strong patterns of differentiation at particular loci. Researchers are also beginning to uncover the genetic architecture of complex diseases, affected by many variants of small effect. The field of population genomics thus holds great potential for providing further insights into the evolution of human disease.

AB - Identifying the causes of similarities and differences in genetic disease prevalence among humans is central to understanding disease etiology. While present-day humans are not strongly differentiated, vast amounts of genomic data now make it possible to study subtle patterns of genetic variation. This allows us to trace our genomic history thousands of years into the past and its implications for the distribution of disease-associated variants today. Genomic analyses have shown that demographic processes shaped the distribution and frequency of disease-associated variants over time. Furthermore, local adaptation to new environmental conditions-including pathogens-has generated strong patterns of differentiation at particular loci. Researchers are also beginning to uncover the genetic architecture of complex diseases, affected by many variants of small effect. The field of population genomics thus holds great potential for providing further insights into the evolution of human disease.

U2 - 10.1016/j.cell.2019.01.052

DO - 10.1016/j.cell.2019.01.052

M3 - Review

VL - 177

SP - 115

EP - 131

JO - Cell

JF - Cell

SN - 0092-8674

IS - 1

ER -

ID: 59035770