Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases.
Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases.
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DOI：
10.1038/s42255-021-00478-5
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发表时间：
2021-11
影响因子：
20.8
通讯作者：
Inouye M
中科院分区：
文献类型：
--
作者：
Ritchie SC;Lambert SA;Arnold M;Teo SM;Lim S;Scepanovic P;Marten J;Zahid S;Chaffin M;Liu Y;Abraham G;Ouwehand WH;Roberts DJ;Watkins NA;Drew BG;Calkin AC;Di Angelantonio E;Soranzo N;Burgess S;Chapman M;Kathiresan S;Khera AV;Danesh J;Butterworth AS;Inouye M
Cardiometabolic diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome. Polygenic scores (PGS) aggregate these into a metric representing an individual’s genetic predisposition to disease. PGS have shown promise for early risk prediction and there is an open question as to whether PGS can also be used to understand disease biology. Here, we demonstrate that cardiometabolic disease PGS can be used to elucidate the proteins underlying disease pathogenesis. In 3,087 healthy individuals, we found that PGS for coronary artery disease, type 2 diabetes, chronic kidney disease and ischaemic stroke are associated with the levels of 49 plasma proteins. Associations were polygenic in architecture, largely independent of cis and trans protein quantitative trait loci and present for proteins without quantitative trait loci. Over a follow-up of 7.7 years, 28 of these proteins associated with future myocardial infarction or type 2 diabetes events, 16 of which were mediators between polygenic risk and incident disease. Twelve of these were druggable targets with therapeutic potential. Our results demonstrate the potential for PGS to uncover causal disease biology and targets with therapeutic potential, including those that may be missed by approaches utilizing information at a single locus. Ritchie et al. use polygenic scores to identify plasma proteins with causal roles in cardiometabolic disease.
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影响因子：
14.9
作者：
Ghoussaini M;Mountjoy E;Carmona M;Peat G;Schmidt EM;Hercules A;Fumis L;Miranda A;Carvalho-Silva D;Buniello A;Burdett T;Hayhurst J;Baker J;Ferrer J;Gonzalez-Uriarte A;Jupp S;Karim MA;Koscielny G;Machlitt-Northen S;Malangone C;Pendlington ZM;Roncaglia P;Suveges D;Wright D;Vrousgou O;Papa E;Parkinson H;MacArthur JAL;Todd JA;Barrett JC;Schwartzentruber J;Hulcoop DG;Ochoa D;McDonagh EM;Dunham I
通讯作者：
Dunham I
DOI：
10.1016/s0140-6736(17)31928-1
发表时间：
2017-11-25
期刊：
Lancet (London, England)
影响因子：
--
作者：
Di Angelantonio E;Thompson SG;Kaptoge S;Moore C;Walker M;Armitage J;Ouwehand WH;Roberts DJ;Danesh J;INTERVAL Trial Group
通讯作者：
INTERVAL Trial Group
影响因子：
2.1
作者：
Bowden J;Davey Smith G;Haycock PC;Burgess S
通讯作者：
Burgess S
影响因子：
17.1
作者：
Finan C;Gaulton A;Kruger FA;Lumbers RT;Shah T;Engmann J;Galver L;Kelley R;Karlsson A;Santos R;Overington JP;Hingorani AD;Casas JP
通讯作者：
Casas JP
影响因子：
64.5
作者：
Boyle EA;Li YI;Pritchard JK
通讯作者：
Pritchard JK