Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Valentina Iotchkova; Jie Huang; John A Morris; Deepti Jain; Caterina Barbieri; Klaudia Walter; Josine L Min; Lu Chen; William Astle; Massimilian Cocca; Patrick Deelen; Heather Elding; Aliki-Eleni Farmaki; Christopher S Franklin; Mattias Franberg; Tom R Gaunt; Albert Hofman; Tao Jiang; Marcus E Kleber; Genevieve Lachance; Jian'An Luan; Giovanni Malerba; Angela Matchan; Daniel Mead; Yasin Memari; Ioanna Ntalla; Kalliope Panoutsopoulou; Raha Pazoki; John R B Perry; Fernando Rivadeneira; Maria Sabater-Lleal; Bengt Sennblad; So-Youn Shin; Lorraine Southam; Michela Traglia; Freerk Van Dijk; Elisabeth M Van Leeuwen; Gianluigi Zaza; Weihua Zhang; Najaf Amin; Adam Butterworth; John C Chambers; George Dedoussis; Abbas Dehghan; Oscar H Franco; Lude Franke; Mattia Frontini; Giovanni Gambaro; Paolo Gasparini; Anders Hamsten; Aaron Issacs; Jaspal S Kooner; Charles Kooperberg; Claudia Langenberg; Winfried Marz; Robert A Scott; Morris A Swertz; Daniela Toniolo; Andre G Uitterlinden; Cornelia M Van Duijn; Hugh Watkins; Eleftheria Zeggini; Mathew T Maurano; Nicholas J Timpson; Alexander P. Reiner; Paul L. Auer; Nicole Soranzo

doi:10.1038/ng.3668

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Valentina Iotchkova, Jie Huang, John A Morris, Deepti Jain, Caterina Barbieri, Klaudia Walter, Josine L Min, Lu Chen, William Astle, Massimilian Cocca, Patrick Deelen, Heather Elding, Aliki-Eleni Farmaki, Christopher S Franklin, Mattias Franberg, Tom R Gaunt, Albert Hofman, Tao Jiang, Marcus E Kleber, Genevieve LachanceJian'An Luan, Giovanni Malerba, Angela Matchan, Daniel Mead, Yasin Memari, Ioanna Ntalla, Kalliope Panoutsopoulou, Raha Pazoki, John R B Perry, Fernando Rivadeneira, Maria Sabater-Lleal, Bengt Sennblad, So-Youn Shin, Lorraine Southam, Michela Traglia, Freerk Van Dijk, Elisabeth M Van Leeuwen, Gianluigi Zaza, Weihua Zhang, Najaf Amin, Adam Butterworth, John C Chambers, George Dedoussis, Abbas Dehghan, Oscar H Franco, Lude Franke, Mattia Frontini, Giovanni Gambaro, Paolo Gasparini, Anders Hamsten, Aaron Issacs, Jaspal S Kooner, Charles Kooperberg, Claudia Langenberg, Winfried Marz, Robert A Scott, Morris A Swertz, Daniela Toniolo, Andre G Uitterlinden, Cornelia M Van Duijn, Hugh Watkins, Eleftheria Zeggini, Mathew T Maurano, Nicholas J Timpson, Alexander P. Reiner, Paul L. Auer, Nicole Soranzo

Università Cattolica del Sacro Cuore

Risultato della ricerca: Contributo in rivista › Articolo in rivista

41 Citazioni (Scopus)

Abstract

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

Lingua originale	English
pagine (da-a)	1303-1312
Numero di pagine	10
Rivista	Nature Genetics
Volume	48
DOI	https://doi.org/10.1038/ng.3668
Stato di pubblicazione	Pubblicato - 2016

Keywords

Genetics

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Iotchkova, V., Huang, J., Morris, J. A., Jain, D., Barbieri, C., Walter, K., Min, J. L., Chen, L., Astle, W., Cocca, M., Deelen, P., Elding, H., Farmaki, A.-E., Franklin, C. S., Franberg, M., Gaunt, T. R., Hofman, A., Jiang, T., Kleber, M. E., ... Soranzo, N. (2016). Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps. Nature Genetics, 48, 1303-1312. https://doi.org/10.1038/ng.3668

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title = "Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps",

abstract = "Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.",

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author = "Valentina Iotchkova and Jie Huang and Morris, {John A} and Deepti Jain and Caterina Barbieri and Klaudia Walter and Min, {Josine L} and Lu Chen and William Astle and Massimilian Cocca and Patrick Deelen and Heather Elding and Aliki-Eleni Farmaki and Franklin, {Christopher S} and Mattias Franberg and Gaunt, {Tom R} and Albert Hofman and Tao Jiang and Kleber, {Marcus E} and Genevieve Lachance and Jian'An Luan and Giovanni Malerba and Angela Matchan and Daniel Mead and Yasin Memari and Ioanna Ntalla and Kalliope Panoutsopoulou and Raha Pazoki and Perry, {John R B} and Fernando Rivadeneira and Maria Sabater-Lleal and Bengt Sennblad and So-Youn Shin and Lorraine Southam and Michela Traglia and {Van Dijk}, Freerk and {Van Leeuwen}, {Elisabeth M} and Gianluigi Zaza and Weihua Zhang and Najaf Amin and Adam Butterworth and Chambers, {John C} and George Dedoussis and Abbas Dehghan and Franco, {Oscar H} and Lude Franke and Mattia Frontini and Giovanni Gambaro and Paolo Gasparini and Anders Hamsten and Aaron Issacs and Kooner, {Jaspal S} and Charles Kooperberg and Claudia Langenberg and Winfried Marz and Scott, {Robert A} and Swertz, {Morris A} and Daniela Toniolo and Uitterlinden, {Andre G} and {Van Duijn}, {Cornelia M} and Hugh Watkins and Eleftheria Zeggini and Maurano, {Mathew T} and Timpson, {Nicholas J} and Reiner, {Alexander P.} and Auer, {Paul L.} and Nicole Soranzo",

year = "2016",

doi = "10.1038/ng.3668",

language = "English",

volume = "48",

pages = "1303--1312",

journal = "Nature Genetics",

issn = "1061-4036",

publisher = "Nature Research",

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Iotchkova, V, Huang, J, Morris, JA, Jain, D, Barbieri, C, Walter, K, Min, JL, Chen, L, Astle, W, Cocca, M, Deelen, P, Elding, H, Farmaki, A-E, Franklin, CS, Franberg, M, Gaunt, TR, Hofman, A, Jiang, T, Kleber, ME, Lachance, G, Luan, JA, Malerba, G, Matchan, A, Mead, D, Memari, Y, Ntalla, I, Panoutsopoulou, K, Pazoki, R, Perry, JRB, Rivadeneira, F, Sabater-Lleal, M, Sennblad, B, Shin, S-Y, Southam, L, Traglia, M, Van Dijk, F, Van Leeuwen, EM, Zaza, G, Zhang, W, Amin, N, Butterworth, A, Chambers, JC, Dedoussis, G, Dehghan, A, Franco, OH, Franke, L, Frontini, M, Gambaro, G, Gasparini, P, Hamsten, A, Issacs, A, Kooner, JS, Kooperberg, C, Langenberg, C, Marz, W, Scott, RA, Swertz, MA, Toniolo, D, Uitterlinden, AG, Van Duijn, CM, Watkins, H, Zeggini, E, Maurano, MT, Timpson, NJ, Reiner, AP, Auer, PL & Soranzo, N 2016, 'Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps', Nature Genetics, vol. 48, pagg. 1303-1312. https://doi.org/10.1038/ng.3668

TY - JOUR

T1 - Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

AU - Iotchkova, Valentina

AU - Huang, Jie

AU - Morris, John A

AU - Jain, Deepti

AU - Barbieri, Caterina

AU - Walter, Klaudia

AU - Min, Josine L

AU - Chen, Lu

AU - Astle, William

AU - Cocca, Massimilian

AU - Deelen, Patrick

AU - Elding, Heather

AU - Farmaki, Aliki-Eleni

AU - Franklin, Christopher S

AU - Franberg, Mattias

AU - Gaunt, Tom R

AU - Hofman, Albert

AU - Jiang, Tao

AU - Kleber, Marcus E

AU - Lachance, Genevieve

AU - Luan, Jian'An

AU - Malerba, Giovanni

AU - Matchan, Angela

AU - Mead, Daniel

AU - Memari, Yasin

AU - Ntalla, Ioanna

AU - Panoutsopoulou, Kalliope

AU - Pazoki, Raha

AU - Perry, John R B

AU - Rivadeneira, Fernando

AU - Sabater-Lleal, Maria

AU - Sennblad, Bengt

AU - Shin, So-Youn

AU - Southam, Lorraine

AU - Traglia, Michela

AU - Van Dijk, Freerk

AU - Van Leeuwen, Elisabeth M

AU - Zaza, Gianluigi

AU - Zhang, Weihua

AU - Amin, Najaf

AU - Butterworth, Adam

AU - Chambers, John C

AU - Dedoussis, George

AU - Dehghan, Abbas

AU - Franco, Oscar H

AU - Franke, Lude

AU - Frontini, Mattia

AU - Gambaro, Giovanni

AU - Gasparini, Paolo

AU - Hamsten, Anders

AU - Issacs, Aaron

AU - Kooner, Jaspal S

AU - Kooperberg, Charles

AU - Langenberg, Claudia

AU - Marz, Winfried

AU - Scott, Robert A

AU - Swertz, Morris A

AU - Toniolo, Daniela

AU - Uitterlinden, Andre G

AU - Van Duijn, Cornelia M

AU - Watkins, Hugh

AU - Zeggini, Eleftheria

AU - Maurano, Mathew T

AU - Timpson, Nicholas J

AU - Reiner, Alexander P.

AU - Auer, Paul L.

AU - Soranzo, Nicole

PY - 2016

Y1 - 2016

N2 - Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

AB - Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

KW - Genetics

UR - http://hdl.handle.net/10807/93214

UR - http://www.nature.com/ng/index.html

U2 - 10.1038/ng.3668

DO - 10.1038/ng.3668

M3 - Article

SN - 1061-4036

VL - 48

SP - 1303

EP - 1312

JO - Nature Genetics

JF - Nature Genetics

ER -

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Abstract

Keywords

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