TY - JOUR
T1 - Stroke genetics informs drug discovery and risk prediction across ancestries
AU - The COMPASS Consortium
AU - The INVENT Consortium
AU - The Dutch Parelsnoer Initiative (PSI) Cerebrovascular Disease Study Group
AU - The Estonian Biobank
AU - The PRECISEQ Consortium
AU - The FinnGen Consortium
AU - The NINDS Stroke Genetics Network (SiGN)
AU - The MEGASTROKE Consortium
AU - The SIREN Consortium
AU - The China Kadoorie Biobank Collaborative Group
AU - The VA Million Veteran Program
AU - The International Stroke Genetics Consortium (ISGC)
AU - The Biobank Japan
AU - The CHARGE Consortium
AU - The GIGASTROKE Consortium
AU - Regeneron Genetics Center
AU - The ODYSSEY Study
AU - HUNT All-In Stroke
AU - The SICFAIL Study
AU - The Generacion Study
AU - The Copenhagen City Heart Study
AU - The SMART Study
AU - Clinical Research Collaboration for Stroke in Korea (CRCS-K) and Korea Biobank Array (KBA) Project
AU - Helsinki Stroke Project
AU - Follow-up Studies
AU - EPIC-CVD
AU - Mishra, Aniket
AU - Malik, Rainer
AU - Hachiya, Tsuyoshi
AU - Jürgenson, Tuuli
AU - Namba, Shinichi
AU - Posner, Daniel C.
AU - Kamanu, Frederick K.
AU - Koido, Masaru
AU - Le Grand, Quentin
AU - Shi, Mingyang
AU - He, Yunye
AU - Georgakis, Marios K.
AU - Caro, Ilana
AU - Krebs, Kristi
AU - Liaw, Yi Ching
AU - Vaura, Felix C.
AU - Lin, Kuang
AU - Winsvold, Bendik Slagsvold
AU - Srinivasasainagendra, Vinodh
AU - Parodi, Livia
AU - Bae, Hee Joon
AU - Chauhan, Ganesh
AU - Chong, Michael R.
AU - Tomppo, Liisa
AU - Akinyemi, Rufus
AU - Roshchupkin, Gennady V.
AU - Habib, Naomi
AU - Jee, Yon Ho
AU - Thomassen, Jesper Qvist
AU - Abedi, Vida
AU - Cárcel-Márquez, Jara
AU - Nygaard, Marianne
AU - Leonard, Hampton L.
AU - Yang, Chaojie
AU - Yonova-Doing, Ekaterina
AU - Knol, Maria J.
AU - Lewis, Adam J.
AU - Judy, Renae L.
AU - Ago, Tetsuro
AU - Amouyel, Philippe
AU - Armstrong, Nicole D.
AU - Bakker, Mark K.
AU - Bartz, Traci M.
AU - Bennett, David A.
AU - Bis, Joshua C.
AU - Bordes, Constance
AU - Børte, Sigrid
AU - Cain, Anael
AU - Ridker, Paul M.
AU - Cho, Kelly
AU - Chen, Zhengming
AU - Cruchaga, Carlos
AU - Cole, John W.
AU - de Jager, Phil L.
AU - de Cid, Rafael
AU - Endres, Matthias
AU - Ferreira, Leslie E.
AU - Geerlings, Mirjam I.
AU - Gasca, Natalie C.
AU - Gudnason, Vilmundur
AU - Hata, Jun
AU - He, Jing
AU - Heath, Alicia K.
AU - Ho, Yuk Lam
AU - Havulinna, Aki S.
AU - Hopewell, Jemma C.
AU - Hyacinth, Hyacinth I.
AU - Inouye, Michael
AU - Jacob, Mina A.
AU - Jeon, Christina E.
AU - Jern, Christina
AU - Kamouchi, Masahiro
AU - Keene, Keith L.
AU - Kitazono, Takanari
AU - Kittner, Steven J.
AU - Konuma, Takahiro
AU - Kumar, Amit
AU - Lacaze, Paul
AU - Launer, Lenore J.
AU - Lee, Keon Joo
AU - Lepik, Kaido
AU - Li, Jiang
AU - Li, Liming
AU - Manichaikul, Ani
AU - Markus, Hugh S.
AU - Marston, Nicholas A.
AU - Meitinger, Thomas
AU - Mitchell, Braxton D.
AU - Montellano, Felipe A.
AU - Morisaki, Takayuki
AU - Mosley, Thomas H.
AU - Nalls, Mike A.
AU - Nordestgaard, Børge G.
AU - O’Donnell, Martin J.
AU - Okada, Yukinori
AU - Onland-Moret, N. Charlotte
AU - Ovbiagele, Bruce
AU - Peters, Annette
AU - Psaty, Bruce M.
AU - Rich, Stephen S.
N1 - Publisher Copyright:
© The Author(s) 2022.
PY - 2022/11/3
Y1 - 2022/11/3
N2 - Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
AB - Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
UR - https://www.scopus.com/pages/publications/85141853404
U2 - 10.1038/s41586-022-05165-3
DO - 10.1038/s41586-022-05165-3
M3 - Article
C2 - 36180795
AN - SCOPUS:85141853404
SN - 0028-0836
VL - 611
SP - 115
EP - 123
JO - Nature
JF - Nature
IS - 7934
ER -
SDG 3 Good Health and Well-being