Mapping gene and gene pathways associated with coronary artery disease: a CARDIoGRAM exome and multi-ancestry UK biobank analysis.
Mapping gene and gene pathways associated with coronary artery disease: a CARDIoGRAM exome and multi-ancestry UK biobank analysis.
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DOI:
10.1038/s41598-021-95637-9
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发表时间:
2021-08-12
影响因子:
4.6
通讯作者:
Dupuis J
中科院分区:
文献类型:
--
作者:
Hariharan P;Dupuis J
Coronary artery disease (CAD) genome-wide association studies typically focus on single nucleotide variants (SNVs), and many potentially associated SNVs fail to reach the GWAS significance threshold. We performed gene and pathway-based association (GBA) tests on publicly available Coronary ARtery DIsease Genome wide Replication and Meta-analysis consortium Exome (n = 120,575) and multi ancestry pan UK Biobank study (n = 442,574) summary data using versatile gene-based association study (VEGAS2) and Multi-marker analysis of genomic annotation (MAGMA) to identify novel genes and pathways associated with CAD. We included only exonic SNVs and excluded regulatory regions. VEGAS2 and MAGMA ranked genes and pathways based on aggregated SNV test statistics. We used Bonferroni corrected gene and pathway significance threshold at 3.0 × 10–6 and 1.0 × 10–5, respectively. We also report the top one percent of ranked genes and pathways. We identified 17 top enriched genes with four genes (PCSK9, FAM177, LPL, ARGEF26), reaching statistical significance (p ≤ 3.0 × 10–6) using both GBA tests in two GWAS studies. In addition, our analyses identified ten genes (DUSP13, KCNJ11, CD300LF/RAB37, SLCO1B1, LRRFIP1, QSER1, UBR2, MOB3C, MST1R, and ABCC8) with previously unreported associations with CAD, although none of the single SNV associations within the genes were genome-wide significant. Among the top 1% non-lipid pathways, we detected pathways regulating coagulation, inflammation, neuronal aging, and wound healing.
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影响因子:
64.8
作者:
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者:
Marchini J
影响因子:
30.8
作者:
Lee JJ;Wedow R;Okbay A;Kong E;Maghzian O;Zacher M;Nguyen-Viet TA;Bowers P;Sidorenko J;Karlsson Linnér R;Fontana MA;Kundu T;Lee C;Li H;Li R;Royer R;Timshel PN;Walters RK;Willoughby EA;Yengo L;23andMe Research Team;COGENT (Cognitive Genomics Consortium);Social Science Genetic Association Consortium;Alver M;Bao Y;Clark DW;Day FR;Furlotte NA;Joshi PK;Kemper KE;Kleinman A;Langenberg C;Mägi R;Trampush JW;Verma SS;Wu Y;Lam M;Zhao JH;Zheng Z;Boardman JD;Campbell H;Freese J;Harris KM;Hayward C;Herd P;Kumari M;Lencz T;Luan J;Malhotra AK;Metspalu A;Milani L;Ong KK;Perry JRB;Porteous DJ;Ritchie MD;Smart MC;Smith BH;Tung JY;Wareham NJ;Wilson JF;Beauchamp JP;Conley DC;Esko T;Lehrer SF;Magnusson PKE;Oskarsson S;Pers TH;Robinson MR;Thom K;Watson C;Chabris CF;Meyer MN;Laibson DI;Yang J;Johannesson M;Koellinger PD;Turley P;Visscher PM;Benjamin DJ;Cesarini D
通讯作者:
Cesarini D
影响因子:
3.7
作者:
Comuzzie AG;Cole SA;Laston SL;Voruganti VS;Haack K;Gibbs RA;Butte NF
通讯作者:
Butte NF
影响因子:
14.8
作者:
Kumar, Prateek;Henikoff, Steven;Ng, Pauline C.
通讯作者:
Ng, Pauline C.
影响因子:
30.8
作者:
Howson JMM;Zhao W;Barnes DR;Ho WK;Young R;Paul DS;Waite LL;Freitag DF;Fauman EB;Salfati EL;Sun BB;Eicher JD;Johnson AD;Sheu WHH;Nielsen SF;Lin WY;Surendran P;Malarstig A;Wilk JB;Tybjærg-Hansen A;Rasmussen KL;Kamstrup PR;Deloukas P;Erdmann J;Kathiresan S;Samani NJ;Schunkert H;Watkins H;CARDIoGRAMplusC4D;Do R;Rader DJ;Johnson JA;Hazen SL;Quyyumi AA;Spertus JA;Pepine CJ;Franceschini N;Justice A;Reiner AP;Buyske S;Hindorff LA;Carty CL;North KE;Kooperberg C;Boerwinkle E;Young K;Graff M;Peters U;Absher D;Hsiung CA;Lee WJ;Taylor KD;Chen YH;Lee IT;Guo X;Chung RH;Hung YJ;Rotter JI;Juang JJ;Quertermous T;Wang TD;Rasheed A;Frossard P;Alam DS;Majumder AAS;Di Angelantonio E;Chowdhury R;EPIC-CVD;Chen YI;Nordestgaard BG;Assimes TL;Danesh J;Butterworth AS;Saleheen D
通讯作者:
Saleheen D