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1. Stroke genetics informs drug discovery and risk prediction across ancestries

Author

Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, Gravel, S, Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, and Gravel, S

Abstract

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.

Published
2022

2. Stroke genetics informs drug discovery and risk prediction across ancestries (vol 611, pg 115, 2022)

Author

Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, IH, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, IH, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, and Debette, S

Published
2022

3. Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries (Nature, (2022), 611, 7934, (115-123), 10.1038/s41586-022-05165-3)

Author

Mishra, A, Malik, R, Hachiya, T, Jürgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, YC, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, HJ, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Cárcel-Márquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Børte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, YL, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, KJ, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O’Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Mishra, A, Malik, R, Hachiya, T, Jürgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, YC, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, HJ, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Cárcel-Márquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Børte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, YL, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, KJ, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O’Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, and Rich, SS

Abstract

In the version of this article initially published, the name of the PRECISE4Q Consortium was misspelled as “PRECISEQ” and has now been amended in the HTML and PDF versions of the article. Further, data in the first column of Supplementary Table 55 were mistakenly shifted and have been corrected in the file accompanying the HTML version of the article.

Published
2022

4. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes (vol 50, pg 524, 2018)

Author

Malik, R, Chauhan, G, Traylor, M, Sargurupremraj, M, Okada, Y, Mishra, A, Rutten-Jacobs, L, Giese, A-K, Van der Laan, SW, Gretarsdottir, S, Anderson, CD, Chong, M, Adams, HHH, Ago, T, Almgren, P, Amouyel, P, Ay, H, Bartz, TM, Benavente, OR, Bevan, S, Boncoraglio, GB, Brown, RD, Butterworth, AS, Carrera, C, Carty, CL, Chasman, DI, Chen, W-M, Cole, JW, Correa, A, Cotlarciuc, I, Cruchaga, C, Danesh, J, De Bakker, PIW, DeStefano, AL, Den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gottesman, RF, Grewal, RP, Gudnason, V, Gustafsson, S, Haessler, J, Harris, TB, Hassan, A, Havulinna, AS, Heckbert, SR, Holliday, EG, Howard, G, Hsu, F-C, Hyacinth, IH, Ikram, MA, Ingelsson, E, Irvin, MR, Jian, X, Jimenez-Conde, J, Johnson, JA, Jukema, JW, Kanai, M, Keene, KL, Kissela, BM, Kleindorfer, DO, Kooperberg, C, Kubo, M, Lange, LA, Langefeld, CD, Langenberg, C, Launer, LJ, Lee, J-M, Lemmens, R, Leys, D, Lewis, CM, Lin, W-Y, Lindgren, AG, Lorentzen, E, Magnusson, PK, Maguire, J, Manichaikul, A, McArdle, PF, Meschia, JF, Mitchell, BD, Mosley, TH, Nalls, MA, Ninomiya, T, O'Donnell, MJ, Psaty, BM, Pulit, SL, Rannikmae, K, Reiner, AP, Rexrode, KM, Rice, K, Rich, SS, Ridker, PM, Rost, NS, Rothwell, PM, Rotter, JI, Rundek, T, Sacco, RL, Sakaue, S, Sale, MM, Salomaa, V, Sapkota, BR, Schmidt, R, Schmidt, CO, Schminke, U, Sharma, P, Slowik, A, Sudlow, CLM, Tanislav, C, Tatlisumak, T, Taylor, KD, Thijs, VNS, Thorleifsson, G, Thorsteinsdottir, U, Tiedt, S, Trompet, S, Tzourio, C, Van Duijn, CM, Walters, M, Wareham, NJ, Wassertheil-Smoller, S, Wilson, JG, Wiggins, KL, Yang, Q, Yusuf, S, Bis, JC, Pastinen, T, Ruusalepp, A, Schadt, EE, Koplev, S, Bjorkegren, JLM, Codoni, V, Civelek, M, Smith, NL, Tregouet, DA, Christophersen, IE, Roselli, C, Lubitz, SA, Ellinor, PT, Tai, ES, Kooner, JS, Kato, N, He, J, Van der Harst, P, Elliott, P, Chambers, JC, Takeuchi, F, Johnson, AD, Sanghera, DK, Melander, O, Jern, C, Strbian, D, Fernandez-Cadenas, I, Longstreth, WT, Rolfs, A, Hata, J, Woo, D, Rosand, J, Pare, G, Hopewell, JC, Saleheen, D, Stefansson, K, Worrall, BB, Kittner, SJ, Seshadri, S, Fornage, M, Markus, HS, Howson, JMM, Kamatani, Y, Debette, S, and Dichgans, M

Subjects
Genetics & Heredity, International Genomics of Blood Pressure (iGEN-BP) Consortium, COMPASS Consortium, MEGASTROKE Consortium, Science & Technology, UK Young Lacunar DNA Study, AFGen Consortium, INVENT Consortium, STARNET, 06 Biological Sciences, METASTROKE Consortium, EPIC-CVD Consortium, BioBank Japan Cooperative Hospital Group, International Stroke Genetics Consortium (ISGC), NINDS Stroke Genetics Network (SiGN), Neurology Working Group of the CHARGE Consortium, EPIC-InterAct Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, Life Sciences & Biomedicine, 11 Medical and Health Sciences, Developmental Biology
Published
2019

5. Serum magnesium and calcium levels in relation to ischemic stroke: Mendelian randomization study

Author

Larsson, SC, Traylor, M, Burgess, S, Boncoraglio, GB, Jern, C, Michaëlsson, K, Markus, HS, Malik, R, Chauhan, G, Sargurupremraj, M, Okada, Y, Mishra, A, Rutten-Jacobs, L, Giese, AK, Van Der Laan, SW, Gretarsdottir, S, Anderson, CD, Chong, M, Adams, HHH, Ago, T, Almgren, P, Amouyel, P, Ay, H, Bartz, RM, Benavente, OR, Bevan, S, Brown, RD, Butterworth, AS, Carrera, C, Carty, CL, Chasman, DI, Chen, WM, Cole, JW, Correa, A, Cotlarciuc, I, Cruchaga, C, Danesh, J, De Bakker, PIW, Destefano, AL, Hoed, MD, Duan, Q, Engelter, ST, Falcone, GJ, Gottesman, RF, Grewal, RP, Gudnason, V, Gustafsson, S, Haessler, J, Harris, TB, Hassan, A, Havulinna, AS, Heckbert, SR, Holliday, EG, Howard, G, Hsu, FC, Hyacinth, HI, Ikram, MA, Ingelsson, E, Irvin, MR, Jian, X, Jiménez-Conde, J, Johnson, JA, Jukema, JW, Kanai, M, Keene, KL, Kissela, BM, Kleindorfer, DO, Kooperberg, C, Kubo, M, Lange, LA, Langefeld, CD, Langenberg, C, Launer, LJ, Lee, JM, Lemmens, R, Leys, D, Lewis, CM, Lin, WY, Lindgren, AG, Lorentzen, E, Magnusson, PK, Maguire, J, Manichaikul, A, McArdle, PF, Meschia, JF, Mitchell, BD, Mosley, TH, Nalls, MA, Ninomiya, T, O'Donnell, MJ, Psaty, BM, Pulit, SL, Rannikmäe, K, Reiner, AP, Rexrode, KM, Rice, K, Rich, SS, Ridker, PM, Rost, NS, Rothwell, PM, Larsson, SC, Traylor, M, Burgess, S, Boncoraglio, GB, Jern, C, Michaëlsson, K, Markus, HS, Malik, R, Chauhan, G, Sargurupremraj, M, Okada, Y, Mishra, A, Rutten-Jacobs, L, Giese, AK, Van Der Laan, SW, Gretarsdottir, S, Anderson, CD, Chong, M, Adams, HHH, Ago, T, Almgren, P, Amouyel, P, Ay, H, Bartz, RM, Benavente, OR, Bevan, S, Brown, RD, Butterworth, AS, Carrera, C, Carty, CL, Chasman, DI, Chen, WM, Cole, JW, Correa, A, Cotlarciuc, I, Cruchaga, C, Danesh, J, De Bakker, PIW, Destefano, AL, Hoed, MD, Duan, Q, Engelter, ST, Falcone, GJ, Gottesman, RF, Grewal, RP, Gudnason, V, Gustafsson, S, Haessler, J, Harris, TB, Hassan, A, Havulinna, AS, Heckbert, SR, Holliday, EG, Howard, G, Hsu, FC, Hyacinth, HI, Ikram, MA, Ingelsson, E, Irvin, MR, Jian, X, Jiménez-Conde, J, Johnson, JA, Jukema, JW, Kanai, M, Keene, KL, Kissela, BM, Kleindorfer, DO, Kooperberg, C, Kubo, M, Lange, LA, Langefeld, CD, Langenberg, C, Launer, LJ, Lee, JM, Lemmens, R, Leys, D, Lewis, CM, Lin, WY, Lindgren, AG, Lorentzen, E, Magnusson, PK, Maguire, J, Manichaikul, A, McArdle, PF, Meschia, JF, Mitchell, BD, Mosley, TH, Nalls, MA, Ninomiya, T, O'Donnell, MJ, Psaty, BM, Pulit, SL, Rannikmäe, K, Reiner, AP, Rexrode, KM, Rice, K, Rich, SS, Ridker, PM, Rost, NS, and Rothwell, PM

Abstract

© 2019 American Academy of Neurology. ObjectiveTo determine whether serum magnesium and calcium concentrations are causally associated with ischemic stroke or any of its subtypes using the mendelian randomization approach.MethodsAnalyses were conducted using summary statistics data for 13 single-nucleotide polymorphisms robustly associated with serum magnesium (n = 6) or serum calcium (n = 7) concentrations. The corresponding data for ischemic stroke were obtained from the MEGASTROKE consortium (34,217 cases and 404,630 noncases).ResultsIn standard mendelian randomization analysis, the odds ratios for each 0.1 mmol/L (about 1 SD) increase in genetically predicted serum magnesium concentrations were 0.78 (95% confidence interval [CI] 0.69-0.89; p = 1.3 × 10-4) for all ischemic stroke, 0.63 (95% CI 0.50-0.80; p = 1.6 × 10-4) for cardioembolic stroke, and 0.60 (95% CI 0.44-0.82; p = 0.001) for large artery stroke; there was no association with small vessel stroke (odds ratio 0.90, 95% CI 0.67-1.20; p = 0.46). Only the association with cardioembolic stroke was robust in sensitivity analyses. There was no association of genetically predicted serum calcium concentrations with all ischemic stroke (per 0.5 mg/dL [about 1 SD] increase in serum calcium: odds ratio 1.03, 95% CI 0.88-1.21) or with any subtype.ConclusionsThis study found that genetically higher serum magnesium concentrations are associated with a reduced risk of cardioembolic stroke but found no significant association of genetically higher serum calcium concentrations with any ischemic stroke subtype.

Published
2019

6. Serum magnesium and calcium levels in relation to ischemic stroke: Mendelian randomization study

Author

Larsson, SC, Traylor, M, Burgess, S, Boncoraglio, GB, Jern, C, Michaëlsson, K, Markus, HS, Malik, R, Chauhan, G, Sargurupremraj, M, Okada, Y, Mishra, A, Rutten-Jacobs, L, Giese, AK, Van Der Laan, SW, Gretarsdottir, S, Anderson, CD, Chong, M, Adams, HHH, Ago, T, Almgren, P, Amouyel, P, Ay, H, Bartz, RM, Benavente, OR, Bevan, S, Brown, RD, Butterworth, AS, Carrera, C, Carty, CL, Chasman, DI, Chen, WM, Cole, JW, Correa, A, Cotlarciuc, I, Cruchaga, C, Danesh, J, De Bakker, PIW, Destefano, AL, Hoed, MD, Duan, Q, Engelter, ST, Falcone, GJ, Gottesman, RF, Grewal, RP, Gudnason, V, Gustafsson, S, Haessler, J, Harris, TB, Hassan, A, Havulinna, AS, Heckbert, SR, Holliday, EG, Howard, G, Hsu, FC, Hyacinth, HI, Ikram, MA, Ingelsson, E, Irvin, MR, Jian, X, Jiménez-Conde, J, Johnson, JA, Jukema, JW, Kanai, M, Keene, KL, Kissela, BM, Kleindorfer, DO, Kooperberg, C, Kubo, M, Lange, LA, Langefeld, CD, Langenberg, C, Launer, LJ, Lee, JM, Lemmens, R, Leys, D, Lewis, CM, Lin, WY, Lindgren, AG, Lorentzen, E, Magnusson, PK, Maguire, J, Manichaikul, A, McArdle, PF, Meschia, JF, Mitchell, BD, Mosley, TH, Nalls, MA, Ninomiya, T, O'Donnell, MJ, Psaty, BM, Pulit, SL, Rannikmäe, K, Reiner, AP, Rexrode, KM, Rice, K, Rich, SS, Ridker, PM, Rost, NS, and Rothwell, PM

Subjects
Stroke, Neurology & Neurosurgery, Intracranial Embolism, Humans, Calcium, Magnesium, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Brain Ischemia
Abstract

© 2019 American Academy of Neurology. ObjectiveTo determine whether serum magnesium and calcium concentrations are causally associated with ischemic stroke or any of its subtypes using the mendelian randomization approach.MethodsAnalyses were conducted using summary statistics data for 13 single-nucleotide polymorphisms robustly associated with serum magnesium (n = 6) or serum calcium (n = 7) concentrations. The corresponding data for ischemic stroke were obtained from the MEGASTROKE consortium (34,217 cases and 404,630 noncases).ResultsIn standard mendelian randomization analysis, the odds ratios for each 0.1 mmol/L (about 1 SD) increase in genetically predicted serum magnesium concentrations were 0.78 (95% confidence interval [CI] 0.69-0.89; p = 1.3 × 10-4) for all ischemic stroke, 0.63 (95% CI 0.50-0.80; p = 1.6 × 10-4) for cardioembolic stroke, and 0.60 (95% CI 0.44-0.82; p = 0.001) for large artery stroke; there was no association with small vessel stroke (odds ratio 0.90, 95% CI 0.67-1.20; p = 0.46). Only the association with cardioembolic stroke was robust in sensitivity analyses. There was no association of genetically predicted serum calcium concentrations with all ischemic stroke (per 0.5 mg/dL [about 1 SD] increase in serum calcium: odds ratio 1.03, 95% CI 0.88-1.21) or with any subtype.ConclusionsThis study found that genetically higher serum magnesium concentrations are associated with a reduced risk of cardioembolic stroke but found no significant association of genetically higher serum calcium concentrations with any ischemic stroke subtype.

Published
2018

7. Publisher correction: Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes(Nature Genetics, (2018) 50, 4, (524-537), 10.1038/s41588-018-0058-3)

Author

Malik, R, Chauhan, G, Traylor, M, Sargurupremraj, M, Okada, Y, Mishra, A, Rutten-Jacobs, L, Giese, AK, van der Laan, SW, Gretarsdottir, S, Anderson, CD, Chong, M, Adams, HHH, Ago, T, Almgren, P, Amouyel, P, Ay, H, Bartz, TM, Benavente, OR, Bevan, S, Boncoraglio, GB, Brown, RD, Butterworth, AS, Carrera, C, Carty, CL, Chasman, DI, Chen, WM, Cole, JW, Correa, A, Cotlarciuc, I, Cruchaga, C, Danesh, J, de Bakker, PIW, Destefano, AL, Den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gottesman, RF, Grewal, RP, Gudnason, V, Gustafsson, S, Haessler, J, Harris, TB, Hassan, A, Havulinna, AS, Heckbert, SR, Holliday, EG, Howard, G, Hsu, FC, Hyacinth, HI, Arfan Ikram, M, Ingelsson, E, Irvin, MR, Jian, X, Jiménez-Conde, J, Johnson, JA, Wouter Jukema, J, Kanai, M, Keene, KL, Kissela, BM, Kleindorfer, DO, Kooperberg, C, Kubo, M, Lange, LA, Langefeld, CD, Langenberg, C, Launer, LJ, Lee, JM, Lemmens, R, Leys, D, Lewis, CM, Lin, WY, Lindgren, AG, Lorentzen, E, Magnusson, PK, Maguire, J, Manichaikul, A, McArdle, PF, Meschia, JF, Mitchell, BD, Mosley, TH, Nalls, MA, Ninomiya, T, O’donnell, MJ, Psaty, BM, Pulit, SL, Rannikmäe, K, Reiner, AP, Rexrode, KM, Rice, K, Rich, SS, Ridker, PM, Rost, NS, Rothwell, PM, Rotter, JI, Rundek, T, Sacco, RL, Sakaue, S, and Sale, MM

Subjects
Developmental Biology
Abstract

© 2019, Nature Publishing Group. All rights reserved. In the HTML version of this article initially published, the author groups ‘AFGen Consortium’, ‘Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium’, ‘International Genomics of Blood Pressure (iGEN-BP) Consortium’, ‘INVENT Consortium’, ‘STARNET’, ‘BioBank Japan Cooperative Hospital Group’, ‘COMPASS Consortium’, ‘EPIC-CVD Consortium’, ‘EPIC-InterAct Consortium’, ‘International Stroke Genetics Consortium (ISGC)’, ‘METASTROKE Consortium’, ‘Neurology Working Group of the CHARGE Consortium’, ‘NINDS Stroke Genetics Network (SiGN)’, ‘UK Young Lacunar DNA Study’ and ‘MEGASTROKE Consortium’ appeared at the end of the author list but should have appeared earlier in the list. In addition, the author group ‘MEGASTROKE Consortium’ was duplicated, and its members were not displayed in the ‘Author information’ section. The errors have been corrected in the HTML version of the article.

Published
2018

8. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes

Author

Malik, R, Chauhan, G, Traylor, M, Sargurupremraj, M, Okada, Y, Mishra, A, Rutten-Jacobs, L, Giese, AK, Van Der Laan, SW, Gretarsdottir, S, Anderson, CD, Chong, M, Adams, HHH, Ago, T, Almgren, P, Amouyel, P, Ay, H, Bartz, TM, Benavente, OR, Bevan, S, Boncoraglio, GB, Brown, RD, Butterworth, AS, Carrera, C, Carty, CL, Chasman, DI, Chen, WM, Cole, JW, Correa, A, Cotlarciuc, I, Cruchaga, C, Danesh, J, De Bakker, PIW, Destefano, AL, Den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gottesman, RF, Grewal, RP, Gudnason, V, Gustafsson, S, Haessler, J, Harris, TB, Hassan, A, Havulinna, AS, Heckbert, SR, Holliday, EG, Howard, G, Hsu, FC, Hyacinth, HI, Ikram, MA, Ingelsson, E, Irvin, MR, Jian, X, Jiménez-Conde, J, Johnson, JA, Jukema, JW, Kanai, M, Keene, KL, Kissela, BM, Kleindorfer, DO, Kooperberg, C, Kubo, M, Lange, LA, Langefeld, CD, Langenberg, C, Launer, LJ, Lee, JM, Lemmens, R, Leys, D, Lewis, CM, Lin, WY, Lindgren, AG, Lorentzen, E, Magnusson, PK, Maguire, J, Manichaikul, A, McArdle, PF, Meschia, JF, Mitchell, BD, Mosley, TH, Nalls, MA, Ninomiya, T, O'Donnell, MJ, Psaty, BM, Pulit, SL, Rannikmäe, K, Reiner, AP, Rexrode, KM, Rice, K, Rich, SS, Ridker, PM, Rost, NS, Rothwell, PM, Rotter, JI, Rundek, T, Sacco, RL, Sakaue, S, Sale, MM, Malik, R, Chauhan, G, Traylor, M, Sargurupremraj, M, Okada, Y, Mishra, A, Rutten-Jacobs, L, Giese, AK, Van Der Laan, SW, Gretarsdottir, S, Anderson, CD, Chong, M, Adams, HHH, Ago, T, Almgren, P, Amouyel, P, Ay, H, Bartz, TM, Benavente, OR, Bevan, S, Boncoraglio, GB, Brown, RD, Butterworth, AS, Carrera, C, Carty, CL, Chasman, DI, Chen, WM, Cole, JW, Correa, A, Cotlarciuc, I, Cruchaga, C, Danesh, J, De Bakker, PIW, Destefano, AL, Den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gottesman, RF, Grewal, RP, Gudnason, V, Gustafsson, S, Haessler, J, Harris, TB, Hassan, A, Havulinna, AS, Heckbert, SR, Holliday, EG, Howard, G, Hsu, FC, Hyacinth, HI, Ikram, MA, Ingelsson, E, Irvin, MR, Jian, X, Jiménez-Conde, J, Johnson, JA, Jukema, JW, Kanai, M, Keene, KL, Kissela, BM, Kleindorfer, DO, Kooperberg, C, Kubo, M, Lange, LA, Langefeld, CD, Langenberg, C, Launer, LJ, Lee, JM, Lemmens, R, Leys, D, Lewis, CM, Lin, WY, Lindgren, AG, Lorentzen, E, Magnusson, PK, Maguire, J, Manichaikul, A, McArdle, PF, Meschia, JF, Mitchell, BD, Mosley, TH, Nalls, MA, Ninomiya, T, O'Donnell, MJ, Psaty, BM, Pulit, SL, Rannikmäe, K, Reiner, AP, Rexrode, KM, Rice, K, Rich, SS, Ridker, PM, Rost, NS, Rothwell, PM, Rotter, JI, Rundek, T, Sacco, RL, Sakaue, S, and Sale, MM

Abstract

© 2018 The Author(s). Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.

Published
2018

9. Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function

Author

Pattaro, C, Teumer, A, Gorski, M, Chu, AY, Li, M, Mijatovic, V, Garnaas, M, Tin, A, Sorice, R, Li, Y, Taliun, D, Olden, M, Foster, M, Yang, Q, Chen, M-H, Pers, TH, Johnson, AD, Ko, Y-A, Fuchsberger, C, Tayo, B, Nalls, M, Feitosa, MF, Isaacs, A, Dehghan, A, d'Adamo, P, Adeyemo, A, Dieffenbach, AK, Zonderman, AB, Nolte, IM, van der Most, PJ, Wright, AF, Shuldiner, AR, Morrison, AC, Hofman, A, Smith, AV, Dreisbach, AW, Franke, A, Uitterlinden, AG, Metspalu, A, Tonjes, A, Lupo, A, Robino, A, Johansson, A, Demirkan, A, Kollerits, B, Freedman, BI, Ponte, B, Oostra, BA, Paulweber, B, Kraemer, BK, Mitchell, BD, Buckley, BM, Peralta, CA, Hayward, C, Helmer, C, Rotimi, CN, Shaffer, CM, Mueller, C, Sala, C, van Duijn, CM, Saint-Pierre, A, Ackermann, D, Shriner, D, Ruggiero, D, Toniolo, D, Lu, Y, Cusi, D, Czamara, D, Ellinghaus, D, Siscovick, DS, Ruderfer, D, Gieger, C, Grallert, H, Rochtchina, E, Atkinson, EJ, Holliday, EG, Boerwinkle, E, Salvi, E, Bottinger, EP, Murgia, F, Rivadeneira, F, Ernst, F, Kronenberg, F, Hu, FB, Navis, GJ, Curhan, GC, Ehret, GB, Homuth, G, Coassin, S, Thun, G-A, Pistis, G, Gambaro, G, Malerba, G, Montgomery, GW, Eiriksdottir, G, Jacobs, G, Li, G, Wichmann, H-E, Campbell, H, Schmidt, H, Wallaschofski, H, Voelzke, H, Brenner, H, Kroemer, HK, Kramer, H, Lin, H, Leach, IM, Ford, I, Guessous, I, Rudan, I, Prokopenko, I, Borecki, I, Heid, IM, Kolcic, I, Persico, I, Jukema, JW, Wilson, JF, Felix, JF, Divers, J, Lambert, J-C, Stafford, JM, Gaspoz, J-M, Smith, JA, Faul, JD, Wang, JJ, Ding, J, Hirschhorn, JN, Attia, J, Whitfield, JB, Chalmers, J, Viikari, J, Coresh, J, Denny, JC, Karjalainen, J, Fernandes, JK, Endlich, K, Butterbach, K, Keene, KL, Lohman, K, Portas, L, Launer, LJ, Lyytikaeinen, L-P, Yengo, L, Franke, L, Ferrucci, L, Rose, LM, Kedenko, L, Rao, M, Struchalin, M, Kleber, ME, Cavalieri, M, Haun, M, Cornelis, MC, Ciullo, M, Pirastu, M, de Andrade, M, McEvoy, MA, Woodward, M, Adam, M, Cocca, M, Nauck, M, Imboden, M, Waldenberger, M, Pruijm, M, Metzger, M, Stumvoll, M, Evans, MK, Sale, MM, Kaehoenen, M, Boban, M, Bochud, M, Rheinberger, M, Verweij, N, Bouatia-Naji, N, Martin, NG, Hastie, N, Probst-Hensch, N, Soranzo, N, Devuyst, O, Raitakari, O, Gottesman, O, Franco, OH, Polasek, O, Gasparini, P, Munroe, PB, Ridker, PM, Mitchell, P, Muntner, P, Meisinger, C, Smit, JH, Kovacs, P, Wild, PS, Froguel, P, Rettig, R, Maegi, R, Biffar, R, Schmidt, R, Middelberg, RPS, Carroll, RJ, Penninx, BW, Scott, RJ, Katz, R, Sedaghat, S, Wild, SH, Kardia, SLR, Ulivi, S, Hwang, S-J, Enroth, S, Kloiber, S, Trompet, S, Stengel, B, Hancock, SJ, Turner, ST, Rosas, SE, Stracke, S, Harris, TB, Zeller, T, Zemunik, T, Lehtimaeki, T, Illig, T, Aspelund, T, Nikopensius, T, Esko, T, Tanaka, T, Gyllensten, U, Voelker, U, Emilsson, V, Vitart, V, Aalto, V, Gudnason, V, Chouraki, V, Chen, W-M, Igl, W, Maerz, W, Koenig, W, Lieb, W, Loos, RJF, Liu, Y, Snieder, H, Pramstaller, PP, Parsa, A, O'Connell, JR, Susztak, K, Hamet, P, Tremblay, J, de Boer, IH, Boeger, CA, Goessling, W, Chasman, DI, Koettgen, A, Kao, WHL, Fox, CS, Pattaro, C, Teumer, A, Gorski, M, Chu, AY, Li, M, Mijatovic, V, Garnaas, M, Tin, A, Sorice, R, Li, Y, Taliun, D, Olden, M, Foster, M, Yang, Q, Chen, M-H, Pers, TH, Johnson, AD, Ko, Y-A, Fuchsberger, C, Tayo, B, Nalls, M, Feitosa, MF, Isaacs, A, Dehghan, A, d'Adamo, P, Adeyemo, A, Dieffenbach, AK, Zonderman, AB, Nolte, IM, van der Most, PJ, Wright, AF, Shuldiner, AR, Morrison, AC, Hofman, A, Smith, AV, Dreisbach, AW, Franke, A, Uitterlinden, AG, Metspalu, A, Tonjes, A, Lupo, A, Robino, A, Johansson, A, Demirkan, A, Kollerits, B, Freedman, BI, Ponte, B, Oostra, BA, Paulweber, B, Kraemer, BK, Mitchell, BD, Buckley, BM, Peralta, CA, Hayward, C, Helmer, C, Rotimi, CN, Shaffer, CM, Mueller, C, Sala, C, van Duijn, CM, Saint-Pierre, A, Ackermann, D, Shriner, D, Ruggiero, D, Toniolo, D, Lu, Y, Cusi, D, Czamara, D, Ellinghaus, D, Siscovick, DS, Ruderfer, D, Gieger, C, Grallert, H, Rochtchina, E, Atkinson, EJ, Holliday, EG, Boerwinkle, E, Salvi, E, Bottinger, EP, Murgia, F, Rivadeneira, F, Ernst, F, Kronenberg, F, Hu, FB, Navis, GJ, Curhan, GC, Ehret, GB, Homuth, G, Coassin, S, Thun, G-A, Pistis, G, Gambaro, G, Malerba, G, Montgomery, GW, Eiriksdottir, G, Jacobs, G, Li, G, Wichmann, H-E, Campbell, H, Schmidt, H, Wallaschofski, H, Voelzke, H, Brenner, H, Kroemer, HK, Kramer, H, Lin, H, Leach, IM, Ford, I, Guessous, I, Rudan, I, Prokopenko, I, Borecki, I, Heid, IM, Kolcic, I, Persico, I, Jukema, JW, Wilson, JF, Felix, JF, Divers, J, Lambert, J-C, Stafford, JM, Gaspoz, J-M, Smith, JA, Faul, JD, Wang, JJ, Ding, J, Hirschhorn, JN, Attia, J, Whitfield, JB, Chalmers, J, Viikari, J, Coresh, J, Denny, JC, Karjalainen, J, Fernandes, JK, Endlich, K, Butterbach, K, Keene, KL, Lohman, K, Portas, L, Launer, LJ, Lyytikaeinen, L-P, Yengo, L, Franke, L, Ferrucci, L, Rose, LM, Kedenko, L, Rao, M, Struchalin, M, Kleber, ME, Cavalieri, M, Haun, M, Cornelis, MC, Ciullo, M, Pirastu, M, de Andrade, M, McEvoy, MA, Woodward, M, Adam, M, Cocca, M, Nauck, M, Imboden, M, Waldenberger, M, Pruijm, M, Metzger, M, Stumvoll, M, Evans, MK, Sale, MM, Kaehoenen, M, Boban, M, Bochud, M, Rheinberger, M, Verweij, N, Bouatia-Naji, N, Martin, NG, Hastie, N, Probst-Hensch, N, Soranzo, N, Devuyst, O, Raitakari, O, Gottesman, O, Franco, OH, Polasek, O, Gasparini, P, Munroe, PB, Ridker, PM, Mitchell, P, Muntner, P, Meisinger, C, Smit, JH, Kovacs, P, Wild, PS, Froguel, P, Rettig, R, Maegi, R, Biffar, R, Schmidt, R, Middelberg, RPS, Carroll, RJ, Penninx, BW, Scott, RJ, Katz, R, Sedaghat, S, Wild, SH, Kardia, SLR, Ulivi, S, Hwang, S-J, Enroth, S, Kloiber, S, Trompet, S, Stengel, B, Hancock, SJ, Turner, ST, Rosas, SE, Stracke, S, Harris, TB, Zeller, T, Zemunik, T, Lehtimaeki, T, Illig, T, Aspelund, T, Nikopensius, T, Esko, T, Tanaka, T, Gyllensten, U, Voelker, U, Emilsson, V, Vitart, V, Aalto, V, Gudnason, V, Chouraki, V, Chen, W-M, Igl, W, Maerz, W, Koenig, W, Lieb, W, Loos, RJF, Liu, Y, Snieder, H, Pramstaller, PP, Parsa, A, O'Connell, JR, Susztak, K, Hamet, P, Tremblay, J, de Boer, IH, Boeger, CA, Goessling, W, Chasman, DI, Koettgen, A, Kao, WHL, and Fox, CS

Abstract

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Published
2016

10. Shared genetic susceptibility of vascular-related biomarkers with ischemic and recurrent stroke.

Author

Williams, SR, Hsu, F-C, Keene, KL, Chen, W-M, Nelson, S, Southerland, AM, Madden, EB, Coull, B, Gogarten, SM, Furie, KL, Dzhivhuho, G, Rowles, JL, Mehndiratta, P, Malik, R, Dupuis, J, Lin, H, Seshadri, S, Rich, SS, Sale, MM, Worrall, BB, METASTROKE, The Genomics and Randomized Trials Network (GARNET) Collaborative Research Group, METASTROKE The Genomics and Randomized Trials Network GARNET Collaborative Research Group, Williams, SR, Hsu, F-C, Keene, KL, Chen, W-M, Nelson, S, Southerland, AM, Madden, EB, Coull, B, Gogarten, SM, Furie, KL, Dzhivhuho, G, Rowles, JL, Mehndiratta, P, Malik, R, Dupuis, J, Lin, H, Seshadri, S, Rich, SS, Sale, MM, Worrall, BB, METASTROKE, The Genomics and Randomized Trials Network (GARNET) Collaborative Research Group, and METASTROKE The Genomics and Randomized Trials Network GARNET Collaborative Research Group

Abstract

OBJECTIVE: To investigate the genetic contributors to cerebrovascular disease and variation in biomarkers of ischemic stroke. METHODS: The Vitamin Intervention for Stroke Prevention Trial (VISP) was a randomized, controlled clinical trial of B vitamin supplementation to prevent recurrent stroke, myocardial infarction, or death. VISP collected baseline measures of C-reactive protein (CRP), fibrinogen, creatinine, prothrombin fragments F1+2, thrombin-antithrombin complex, and thrombomodulin prior to treatment initiation. Genome-wide association scans were conducted for these traits and follow-up replication analyses were performed. RESULTS: We detected an association between CRP single nucleotide polymorphisms (SNPs) and circulating CRP levels (most associated SNP, rs2592902, p = 1.14 × 10(-9)) in 2,100 VISP participants. We discovered a novel association for CRP level in the AKR1D1 locus (rs2589998, p = 7.3 × 10(-8), approaching genome-wide significance) that also is an expression quantitative trait locus for CRP gene expression. We replicated previously identified associations of fibrinogen with SNPs in the FGB and LEPR loci. CRP-associated SNPs and CRP levels were significantly associated with risk of ischemic stroke and recurrent stroke in VISP as well as specific stroke subtypes in METASTROKE. Fibrinogen levels but not fibrinogen-associated SNPs were also found to be associated with recurrent stroke in VISP. CONCLUSIONS: Our data identify a genetic contribution to inflammatory and hemostatic biomarkers in a stroke population. Additionally, our results suggest shared genetic contributions to circulating CRP levels measured poststroke and risk for incident and recurrent ischemic stroke. These data broaden our understanding of genetic contributors to biomarker variation and ischemic stroke risk, which should be useful in clinical risk evaluation.

Published
2016

11. Serum magnesium and calcium levels in relation to ischemic stroke Mendelian randomization study

Author

Susanna C. Larsson, Matthew Traylor, Stephen Burgess, Giorgio B. Boncoraglio, Christina Jern, Karl Michaëlsson, Hugh S. Markus, Rainer Malik, Ganesh Chauhan, Muralidharan Sargurupremraj, Yukinori Okada, Aniket Mishra, Loes Rutten-Jacobs, Anne-Katrin Giese, Sander W van der Laan, Solveig Gretarsdottir, Christopher D Anderson, Michael Chong, Hieab HH Adams, Tetsuro Ago, Peter Almgren, Philippe Amouyel, Hakan Ay, raci M Bartz, Oscar R Benavente, Steve Bevan, Giorgio B Boncoraglio, Robert D Brown, Adam S Butterworth, Caty Carrera, Cara L Carty, Daniel I Chasman, Wei-Min Chen, John W Cole, Adolfo Correa, Ioana Cotlarciuc, Carlos Cruchaga, John Danesh, Paul IW de Bakker, Anita L DeStefano, Marcel den Hoed, Qing Duan, Stefan T Engelter, Guido J Falcone, Rebecca F Gottesman, Raji P Grewal, Vilmundur Gudnason, Stefan Gustafsson, Jeffrey Haessler, Tamara B Harris, Ahamad Hassan, Aki S Havulinna, Susan R Heckbert, Elizabeth G Holliday, George Howard, Fang-Chi Hsu, Hyacinth I Hyacinth, M Arfan Ikram, Erik Ingelsson, Marguerite R Irvin, Xueqiu Jian, Jordi Jiménez-Conde, Julie A Johnson, J Wouter Jukema, Masahiro Kanai, Keith L Keene, Brett M Kissela, Dawn O Kleindorfer, Charles Kooperberg, Michiaki Kubo, Leslie A Lange, Carl D Langefeld, Claudia Langenberg, Lenore J Launer, Jin-Moo Lee, Robin Lemmens, Didier Leys, Cathryn M Lewis, Wei-Yu Lin, Arne G Lindgren, Erik Lorentzen, Patrik K Magnusson, Jane Maguire, Ani Manichaikul, Patrick F McArdle, James F Meschia, Braxton D Mitchell, Thomas H Mosley, Michael A Nalls, Toshiharu Ninomiya, Martin J O'Donnell, Bruce M Psaty, Sara L Pulit, Kristiina Rannikmäe, Alexander P Reiner, Kathryn M Rexrode, Kenneth Rice, Stephen S Rich, Paul M Ridker, Natalia S Rost, Peter M Rothwell, Jerome I Rotter, Tatjana Rundek, Ralph L Sacco, Saori Sakaue, Michele M Sale, Veikko Salomaa, Bishwa R Sapkota, Reinhold Schmidt, Carsten O Schmidt, Ulf Schminke, Pankaj Sharma, Agnieszka Slowik, Cathie LM Sudlow, Christian Tanislav, Turgut Tatlisumak, Kent D Taylor, Vincent NS Thijs, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Steffen Tiedt, Stella Trompet, Christophe Tzourio, Cornelia M van Duijn, Matthew Walters, Nicholas J Wareham, Sylvia Wassertheil-Smoller, James G Wilson, Kerri L Wiggins, Qiong Yang, Salim Yusuf, Najaf Amin, Hugo S Aparicio, Donna K Arnett, John Attia, Alexa S Beiser, Claudine Berr, Julie E Buring, Mariana Bustamante, Valeria Caso, Yu-Ching Cheng, Seung Hoan Choi, Ayesha Chowhan, Natalia Cullell, Jean-François Dartigues, Hossein Delavaran, Pilar Delgado, Marcus Dörr, Gunnar Engström, Ian Ford, Wander S Gurpreet, Anders Hamsten, Laura Heitsch, Atsushi Hozawa, Laura Ibanez, Andreea Ilinca, Martin Ingelsson, Motoki Iwasaki, Rebecca D Jackson, Katarina Jood, Pekka Jousilahti, Sara Kaffashian, Lalit Kalra, Masahiro Kamouchi, Takanari Kitazono, Olafur Kjartansson, Manja Kloss, Peter J Koudstaal, Jerzy Krupinski, Daniel L Labovitz, Cathy C Laurie, Christopher R Levi, Linxin Li, Lars Lind, Cecilia M Lindgren, Vasileios Lioutas, Yong Mei Liu, Oscar L Lopez, Hirata Makoto, Nicolas Martinez-Majander, Koichi Matsuda, Naoko Minegishi, Joan Montaner, Andrew P Morris, Elena Muiño, Martina Müller-Nurasyid, Bo Norrving, Soichi Ogishima, Eugenio A Parati, Leema Reddy Peddareddygari, Nancy L Pedersen, Joanna Pera, Markus Perola, Alessandro Pezzini, Silvana Pileggi, Raquel Rabionet, Iolanda Riba-Llena, Marta Ribasés, Jose R Romero, Jaume Roquer, Anthony G Rudd, Antti-Pekka Sarin, Ralhan Sarju, Chloe Sarnowski, Makoto Sasaki, Claudia L Satizabal, Mamoru Satoh, Naveed Sattar, Norie Sawada, Gerli Sibolt, Ásgeir Sigurdsson, Albert Smith, Kenji Sobue, Carolina Soriano-Tárraga, Tara Stanne, O Colin Stine, David J Stott, Konstantin Strauch, Takako Takai, Hideo Tanaka, Kozo Tanno, Alexander Teumer, Liisa Tomppo, Nuria P Torres-Aguila, Emmanuel Touze, Shoichiro Tsugane, Andre G Uitterlinden, Einar M Valdimarsson, Sven J van der Lee, Henry Völzke, Kenji Wakai, David Weir, Stephen R Williams, Charles DA Wolfe, Quenna Wong, Huichun Xu, Taiki Yamaji, Dharambir K Sanghera, Olle Melander, Daniel Strbian, Israel Fernandez-Cadenas, W T Longstreth, Arndt Rolfs, Jun Hata, Daniel Woo, Jonathan Rosand, Guillaume Pare, Jemma C Hopewell, Danish Saleheen, Kari Stefansson, Bradford B Worrall, Steven J Kittner, Sudha Seshadri, Myriam Fornage, Hugh S Markus, Joanna MM Howson, Yoichiro Kamatani, Stephanie Debette, Martin Dichgans, Berr, Claudine, Unit of Cardiovascular and Nutritional Epidemiology [Stockholm, Sweden], Karolinska Institutet [Stockholm]-Institute of Environmental Medicine [Stockholm, Sweden], Stroke Research Group [London, UK] (Department of Brain Repair and Rehabilitation), University of London - UCL [London, UK], MRC Biostatistics Unit [Cambridge, UK], University of Cambridge [UK] (CAM), Department of Public Health and Primary Care [Cambridge, UK] (Institute of Public Health), Fondazione IRCCS Istituto Neurologico 'Carlo Besta', Section of Clinical Immunology [Uppsala, Sweden] (Department of Immunology, Genetics and Pathology), Uppsala University, Department of Surgical Sciences [Uppsala, Sweden], This work was supported by the Swedish Research Council for Health, Working Life and Welfare (Forte) and the Swedish Research Council. Hugh Markus is supported by an NIHR Senior Investigator award. His and Matthew Traylor’s work is supported by infrastructural support from the Cambridge University Hospitals Trust NIHR Biomedical Research Centre., MEGASTROKE project of the International Stroke Genetics Consortium : Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese AK, van der Laan SW, Gretarsdottir S, Anderson CD, Chong M, Adams HH, Ago T, Almgren P, Amouyel P, Ay H, Bartz RM, Benavente OR, Bevan S, Boncoraglio GB, Brown RD Jr, Butterworth AS, Carrera C, Carty CL, Chasman DI, Chen WM, Cole JW, Correa A, Cotlarciuc I, Cruchaga C, Danesh J, de Bakker PI, DeStefano AL, Hoed MD, Duan Q, Engelter ST, Falcone GJ, Gottesman RF, Grewal RP, Gudnason V, Gustafsson S, Haessler J, Harris TB, Hassan A, Havulinna AS, Heckbert SR, Holliday EG, Howard G, Hsu FC, Hyacinth HI, Ikram MA, Ingelsson E, Irvin MR, Jian X, Jiménez-Conde J, Johnson JA, Jukema JW, Kanai M, Keene KL, Kissela BM, Kleindorfer DO, Kooperberg C, Kubo M, Lange LA, Langefeld CD, Langenberg C, Launer LJ, Lee JM, Lemmens R, Leys D, Lewis CM, Lin WY, Lindgren AG, Lorentzen E, Magnusson PK, Maguire J, Manichaikul A, McArdle PF, Meschia JF, Mitchell BD, Mosley TH, Nalls MA, Ninomiya T, O'Donnell MJ, Psaty BM, Pulit SL, Rannikmäe K, Reiner AP, Rexrode KM, Rice K, Rich SS, Ridker PM, Rost NS, Rothwell PM, Rotter JI, Rundek T, Sacco RL, Sakaue S, Sale MM, Salomaa V, Sapkota BR, Schmidt R, Schmidt CO, Schminke U, Sharma P, Slowik A, Sudlow CL, Tanislav C, Tatlisumak T, Taylor KD, Thijs VN, Thorleifsson G, Thorsteinsdottir U, Tiedt S, Trompet S, Tzourio C, van Duijn CM, Walters M, Wareham NJ, Wassertheil-Smoller S, Wilson JG, Wiggins KL, Yang Q, Yusuf S, Amin N, Aparicio HS, Arnett DK, Attia J, Beiser AS, Berr C, Buring JE, Bustamante M, Caso V, Cheng YC, Choi SH, Chowhan A, Cullell N, Dartigues JF, Delavaran H, Delgado P, Dörr M, Engström G, Ford I, Gurpreet WS, Hamsten A, Heitsch L, Hozawa A, Ibanez L, Ilinca A, Ingelsson M, Iwasaki M, Jackson RD, Jood K, Jousilahti P, Kaffashian S, Kalra L, Kamouchi M, Kitazono T, Kjartansson O, Kloss M, Koudstaal PJ, Krupinski J, Labovitz DL, Laurie CC, Levi CR, Li L, Lind L, Lindgren CM, Lioutas V, Liu YM, Lopez OL, Makoto H, Martinez-Majander N, Matsuda K, Minegishi N, Montaner J, Morris AP, Muiño E, Müller-Nurasyid M, Norrving B, Ogishima S, Parati EA, Peddareddygari LR, Pedersen NL, Pera J, Perola M, Pezzini A, Pileggi S, Rabionet R, Riba-Llena I, Ribasés M, Romero JR, Roquer J, Rudd AG, Sarin AP, Sarju R, Sarnowski C, Sasaki M, Satizabal CL, Satoh M, Sattar N, Sawada N, Sibolt G, Sigurdsson Á, Smith A, Sobue K, Soriano-Tárraga C, Stanne T, Stine OC, Stott DJ, Strauch K, Takai T, Tanaka H, Tanno K, Teumer A, Tomppo L, Torres-Aguila NP, Touze E, Tsugane S, Uitterlinden AG, Valdimarsson EM, van der Lee SJ, Völzke H, Wakai K, Weir D, Williams SR, Wolfe CD, Wong Q, Xu H, Yamaji T, Sanghera DK, Melander O, Jern C, Strbian D, Fernandez-Cadenas I, Longstreth WT Jr, Rolfs A, Hata J, Woo D, Rosand J, Pare G, Hopewell JC, Saleheen D, Stefansson K, Worrall BB, Kittner SJ, Seshadri S, Fornage M, Markus HS, Howson JM, Kamatani Y, Debette S, Dichgans M., Larsson, Susanna C [0000-0003-0118-0341], Apollo - University of Cambridge Repository, and Neurology

Subjects
medicine.medical_specialty, Neurology, Heredity, Neurologi, [SDV]Life Sciences [q-bio], chemistry.chemical_element, Calcium, Polymorphism, Single Nucleotide, Gastroenterology, Article, Brain Ischemia, Brain ischemia, 03 medical and health sciences, 0302 clinical medicine, Human genetics, Internal medicine, Mendelian randomization, Medicine, Humans, Magnesium, 030212 general & internal medicine, Stroke, Herència (Biologia), Genètica humana, business.industry, Neurosciences, Mendelian Randomization Analysis, Odds ratio, medicine.disease, Confidence interval, 3. Good health, [SDV] Life Sciences [q-bio], Intracranial Embolism, chemistry, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Neurology (clinical), business, 030217 neurology & neurosurgery, Neurovetenskaper
Abstract

Comment inThe yin and yang of magnesium and calcium: New genetic insights for stroke? [Neurology. 2019]; International audience; Objective To determine whether serum magnesium and calcium concentrations are causally associated with ischemic stroke or any of its subtypes using the mendelian randomization approach. Methods Analyses were conducted using summary statistics data for 13 single-nucleotide polymorphisms robustly associated with serum magnesium (n = 6) or serum calcium (n = 7) concentrations. The corresponding data for ischemic stroke were obtained from the MEGASTROKE consortium (34,217 cases and 404,630 noncases). Results In standard mendelian randomization analysis, the odds ratios for each 0.1 mmol/L (about 1 SD) increase in genetically predicted serum magnesium concentrations were 0.78 (95% confidence interval [CI] 0.69-0.89; p = 1.3 × 10 −4) for all ischemic stroke, 0.63 (95% CI 0.50-0.80; p = 1.6 × 10 −4) for cardioembolic stroke, and 0.60 (95% CI 0.44-0.82; p = 0.001) for large artery stroke; there was no association with small vessel stroke (odds ratio 0.90, 95% CI 0.67-1.20; p = 0.46). Only the association with cardioembolic stroke was robust in sensitivity analyses. There was no association of genetically predicted serum calcium concentrations with all ischemic stroke (per 0.5 mg/dL [about 1 SD] increase in serum calcium: odds ratio 1.03, 95% CI 0.88-1.21) or with any subtype. Conclusions This study found that genetically higher serum magnesium concentrations are associated with a reduced risk of cardioembolic stroke but found no significant association of genetically higher serum calcium concentrations with any ischemic stroke subtype.

Published
2019

12. Organ weights and length anthropometry measures at autopsy for sudden infant death syndrome cases and other infant deaths in the Chicago infant mortality study.

Author

Mychaleckyj JC, Normeshie C, Keene KL, and Hauck FR

Subjects
Female, Humans, Infant, Infant, Newborn, Male, Anthropometry methods, Autopsy, Bayes Theorem, Black or African American, Body Height, Case-Control Studies, Chicago epidemiology, Infant Mortality, Organ Size, Sudden Infant Death epidemiology, Sudden Infant Death etiology, Sudden Infant Death pathology
Abstract

Organ weights are a possible diagnostic or pathophysiological clue to distinguishing sudden infant death syndrome (SIDS) cases from other infant deaths but suffer from major confounding. Using autopsy data from the Chicago Infant Mortality Study, a majority African-American case-control study of deceased infants under 1 year conducted 1993-96, we assessed differences in the weights of brain, thymus, kidneys, lungs, liver, spleen, total body, and four length anthropometry measures in SIDS-diagnosed infants compared to controls. Using exact and coarsened matching, we ran Bayesian linear models with these anthropometry outcomes and repeated the analyses substituting the corresponding fitted allometrically-scaled organ weight indices to account for body size. After detailed analysis and adjustment for potential confounders, we found that matched SIDS infants were generally bigger than controls, with higher mean brain, liver, spleen, thymus, lung, and total body weights, and higher mean head and chest circumference, crown-heel, crown-rump lengths. SIDS infants also had higher mean thymus, liver, spleen, lung and total body weight indices. The association with thymus weight was proportionately greater in magnitude than any other outcome measure and independent of body size. The results of these more detailed analyses are consistent with recent findings from other studies with differing racial compositions, and substantially confirm the primary organ sites for more detailed mechanistic research into the biological dysregulation contributing to underlying pathophysiology of SIDS., (© 2024 The Author(s). American Journal of Human Biology published by Wiley Periodicals LLC.)

Published
2024
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13. Genome-Wide Association Studies of 3 Distinct Recovery Phenotypes in Mild Ischemic Stroke.

Author

Aldridge CM, Braun R, Lohse K, de Havenon A, Cole JW, Cramer SC, Lindgren AG, Keene KL, Hsu FC, and Worrall BB

Subjects
Humans, Male, Aged, Female, Genome-Wide Association Study, Nerve Tissue Proteins, Receptors, Immunologic, Phenotype, Jumonji Domain-Containing Histone Demethylases, ATP-Binding Cassette Transporters, Ischemic Stroke, Stroke genetics
Abstract

Background and Objectives: Stroke genetic research has made substantial progress in the past decade. Its recovery application, however, remains behind, in part due to its reliance on the modified Rankin Scale (mRS) score as a measure of poststroke outcome. The mRS does not map well to biological processes because numerous psychosocial factors drive much of what the mRS captures. Second, the mRS contains multiple disparate biological events into a single measure further limiting its use for biological discovery. This led us to investigate the effect of distinct stroke recovery phenotypes on genetic variation associations with Genome-Wide Association Studies (GWASs) by repurposing the NIH Stroke Scale (NIHSS) and its subscores., Methods: In the Vitamin Intervention for Stroke Prevention cohort, we estimated changes in cognition, motor, and global impairments over 2 years using specific measures. We included genotyped participants with a total NIHSS score greater than zero at randomization and excluded those with recurrent stroke during the trial. A GWAS linear mixed-effects model predicted score changes, with participant as a random effect, and included initial score, age, sex, treatment group, and the first 5 ancestry principal components., Results: In total, 1,270 participants (64% male) were included with a median NIHSS score of 2 (interquartile range [IQR] 1-3) and median age 68 (IQR 59-75) years. At randomization, 20% had cognitive deficits (NIHSS Cog-4 score >0) and 70% had ≥1 motor deficits (impairment score >1). At 2 years, these percentages improved to 7.2% with cognitive deficits and 30% with motor deficits. GWAS identified novel suggestive gene-impairment associations ( p < 5e -6 ) for cognition ( CAMK2D , EVX2 , LINC0143 , PTPRM , SGMS1 , and SMAD2 ), motor ( ACBD6 , KDM4B , MARK4 , PTPRS , ROBO1 , and ROBO2 ), and global ( MSR1 and ROBO2 ) impairments., Discussion: Defining domain-specific stroke recovery phenotypes and using longitudinal clinical trial designs can help detect novel genes associated with chronic recovery. These data support the use of granular endpoints to identify genetic associations related to stroke recovery.

Published
2024
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14. Single Nucleotide Polymorphisms Associated With Motor Recovery in Patients With Nondisabling Stroke: GWAS Study.

Author

Aldridge CM, Braun R, Keene KL, Hsu FC, and Worrall BB

Subjects
Humans, Middle Aged, Aged, Genome-Wide Association Study, Genotype, Phenotype, Polymorphism, Single Nucleotide genetics, Stroke genetics
Abstract

Background and Objectives: Despite notable advances in genetic understanding of stroke recovery, most studies focus only on candidate genes. To date, only 2 genome-wide association studies (GWAS) have focused on stroke outcomes, but they were limited to the modified Rankin Scale (mRS). The mRS maps poorly to biological processes. Therefore, we performed a GWAS to discover single nucleotide polymorphisms (SNPs) associated with motor recovery poststroke., Methods: We used the Vitamin Intervention for Stroke Prevention (VISP) data set of 2,100 genotyped participants with nondisabling stroke. We included only participants who had motor impairment at randomization. Participants with a recurrent stroke during the trial were excluded. Genotyped data underwent strict quality control and imputation. The GWAS used logistic regression models with generalized estimating equations to leverage the repeated NIH Stroke Scale motor score measurements spanning 6 time points over 24 months. The primary outcome was a decrease in the motor drift score of ≥1 vs <1 at each time point. Our model estimated the odds ratio (OR) of motor improvement for each SNP after adjusting for age, sex, race, days from stroke to visit, initial motor score, VISP treatment arm, and principal components., Results: A total of 488 (64%) participants with a mean (SD) age of 66 ± 11 years were included in the GWAS. Although no associations reached genome-wide significance ( p < 5 × 10 -8 ), our analysis detected 115 suggestive associations ( p < 5 × 10 -6 ). Notably, we found multiple SNP clusters near genes with plausible neuronal repair biology mechanisms. The CLDN23 gene had the most convincing association with rs1268196-T as its most significant SNP (OR 0.32; 95% CI 0.21-0.48; p value 6.19 × 10 -7 ). CLDN23 affects blood-brain barrier integrity, neurodevelopment, and immune cell transmigration., Discussion: We identified novel suggestive genetic associations with the first-ever motor-specific poststroke recovery GWAS. The results seem to describe a distinct stroke recovery phenotype compared with prior genetic stroke outcome studies that use outcome measures, such as the mRS. Replication and further mechanistic investigation are warranted. In addition, this study demonstrated a proof-of-principle approach to optimize statistical efficiency with longitudinal data sets for genetic discovery., (© 2023 American Academy of Neurology.)

Published
2023
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15. Post Stroke Motor Recovery Genome Wide Association Study: A Domain-Specific Approach .

Author

Aldridge CM, Robynne B, Keene KL, Hsu FC, Sale MM, and Worrall BB

Abstract

Background: In this genome wide association study (GWAS) we aimed to discover single nucleotide polymorphisms (SNPs) associated with motor recovery post-stroke., Methods: We used the Vitamin Intervention for Stroke Prevention (VISP) dataset of 2,100 genotyped patients with non-disabling stroke. Of these, 488 patients had motor impairment at enrollment. Genotyped data underwent strict quality control and imputation. The GWAS utilized logistic regression models with generalized estimating equations (GEE) to leverage the repeated NIH Stroke Scale (NIHSS) motor score measurements spanning 6 time points over 24 months. The primary outcome was a decrease in the motor drift score of ≥ 1 vs. < 1 at each timepoint. Our model estimated the odds ratio of motor improvement for each SNP after adjusting for age, sex, race, days from stroke to visit, initial motor score, VISP treatment arm, and principal components., Results: Although no associations reached genome-wide significance (p < 5 × 10 -8 ), our analysis detected 115 suggestive associations (p < 5 × 10 -6 ). Notably, we found multiple SNP clusters near genes with plausible neuronal repair biology mechanisms. The CLDN23 gene had the most convincing association which affects blood-brain barrier integrity, neurodevelopment, and immune cell transmigration., Conclusion: We identified novel suggestive genetic associations with the first ever motor-specific post stroke recovery GWAS. The results seem to describe a distinct stroke recovery phenotype compared to prior genetic stroke outcome studies that use outcome measures, like the mRS. Replication and further mechanistic investigation are warranted. Additionally, this study demonstrated a proof-of-principle approach to optimize statistical efficiency with longitudinal datasets for genetic discovery.

Published
2023
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16. Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries.

Author

Mishra A, Malik R, Hachiya T, Jürgenson T, Namba S, Posner DC, Kamanu FK, Koido M, Le Grand Q, Shi M, He Y, Georgakis MK, Caro I, Krebs K, Liaw YC, Vaura FC, Lin K, Winsvold BS, Srinivasasainagendra V, Parodi L, Bae HJ, Chauhan G, Chong MR, Tomppo L, Akinyemi R, Roshchupkin GV, Habib N, Jee YH, Thomassen JQ, Abedi V, Cárcel-Márquez J, Nygaard M, Leonard HL, Yang C, Yonova-Doing E, Knol MJ, Lewis AJ, Judy RL, Ago T, Amouyel P, Armstrong ND, Bakker MK, Bartz TM, Bennett DA, Bis JC, Bordes C, Børte S, Cain A, Ridker PM, Cho K, Chen Z, Cruchaga C, Cole JW, de Jager PL, de Cid R, Endres M, Ferreira LE, Geerlings MI, Gasca NC, Gudnason V, Hata J, He J, Heath AK, Ho YL, Havulinna AS, Hopewell JC, Hyacinth HI, Inouye M, Jacob MA, Jeon CE, Jern C, Kamouchi M, Keene KL, Kitazono T, Kittner SJ, Konuma T, Kumar A, Lacaze P, Launer LJ, Lee KJ, Lepik K, Li J, Li L, Manichaikul A, Markus HS, Marston NA, Meitinger T, Mitchell BD, Montellano FA, Morisaki T, Mosley TH, Nalls MA, Nordestgaard BG, O'Donnell MJ, Okada Y, Onland-Moret NC, Ovbiagele B, Peters A, Psaty BM, Rich SS, Rosand J, Sabatine MS, Sacco RL, Saleheen D, Sandset EC, Salomaa V, Sargurupremraj M, Sasaki M, Satizabal CL, Schmidt CO, Shimizu A, Smith NL, Sloane KL, Sutoh Y, Sun YV, Tanno K, Tiedt S, Tatlisumak T, Torres-Aguila NP, Tiwari HK, Trégouët DA, Trompet S, Tuladhar AM, Tybjærg-Hansen A, van Vugt M, Vibo R, Verma SS, Wiggins KL, Wennberg P, Woo D, Wilson PWF, Xu H, Yang Q, Yoon K, Millwood IY, Gieger C, Ninomiya T, Grabe HJ, Jukema JW, Rissanen IL, Strbian D, Kim YJ, Chen PH, Mayerhofer E, Howson JMM, Irvin MR, Adams H, Wassertheil-Smoller S, Christensen K, Ikram MA, Rundek T, Worrall BB, Lathrop GM, Riaz M, Simonsick EM, Kõrv J, França PHC, Zand R, Prasad K, Frikke-Schmidt R, de Leeuw FE, Liman T, Haeusler KG, Ruigrok YM, Heuschmann PU, Longstreth WT, Jung KJ, Bastarache L, Paré G, Damrauer SM, Chasman DI, Rotter JI, Anderson CD, Zwart JA, Niiranen TJ, Fornage M, Liaw YP, Seshadri S, Fernández-Cadenas I, Walters RG, Ruff CT, Owolabi MO, Huffman JE, Milani L, Kamatani Y, Dichgans M, and Debette S

Published
2022
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17. Stroke genetics informs drug discovery and risk prediction across ancestries.

Author

Mishra A, Malik R, Hachiya T, Jürgenson T, Namba S, Posner DC, Kamanu FK, Koido M, Le Grand Q, Shi M, He Y, Georgakis MK, Caro I, Krebs K, Liaw YC, Vaura FC, Lin K, Winsvold BS, Srinivasasainagendra V, Parodi L, Bae HJ, Chauhan G, Chong MR, Tomppo L, Akinyemi R, Roshchupkin GV, Habib N, Jee YH, Thomassen JQ, Abedi V, Cárcel-Márquez J, Nygaard M, Leonard HL, Yang C, Yonova-Doing E, Knol MJ, Lewis AJ, Judy RL, Ago T, Amouyel P, Armstrong ND, Bakker MK, Bartz TM, Bennett DA, Bis JC, Bordes C, Børte S, Cain A, Ridker PM, Cho K, Chen Z, Cruchaga C, Cole JW, de Jager PL, de Cid R, Endres M, Ferreira LE, Geerlings MI, Gasca NC, Gudnason V, Hata J, He J, Heath AK, Ho YL, Havulinna AS, Hopewell JC, Hyacinth HI, Inouye M, Jacob MA, Jeon CE, Jern C, Kamouchi M, Keene KL, Kitazono T, Kittner SJ, Konuma T, Kumar A, Lacaze P, Launer LJ, Lee KJ, Lepik K, Li J, Li L, Manichaikul A, Markus HS, Marston NA, Meitinger T, Mitchell BD, Montellano FA, Morisaki T, Mosley TH, Nalls MA, Nordestgaard BG, O'Donnell MJ, Okada Y, Onland-Moret NC, Ovbiagele B, Peters A, Psaty BM, Rich SS, Rosand J, Sabatine MS, Sacco RL, Saleheen D, Sandset EC, Salomaa V, Sargurupremraj M, Sasaki M, Satizabal CL, Schmidt CO, Shimizu A, Smith NL, Sloane KL, Sutoh Y, Sun YV, Tanno K, Tiedt S, Tatlisumak T, Torres-Aguila NP, Tiwari HK, Trégouët DA, Trompet S, Tuladhar AM, Tybjærg-Hansen A, van Vugt M, Vibo R, Verma SS, Wiggins KL, Wennberg P, Woo D, Wilson PWF, Xu H, Yang Q, Yoon K, Millwood IY, Gieger C, Ninomiya T, Grabe HJ, Jukema JW, Rissanen IL, Strbian D, Kim YJ, Chen PH, Mayerhofer E, Howson JMM, Irvin MR, Adams H, Wassertheil-Smoller S, Christensen K, Ikram MA, Rundek T, Worrall BB, Lathrop GM, Riaz M, Simonsick EM, Kõrv J, França PHC, Zand R, Prasad K, Frikke-Schmidt R, de Leeuw FE, Liman T, Haeusler KG, Ruigrok YM, Heuschmann PU, Longstreth WT, Jung KJ, Bastarache L, Paré G, Damrauer SM, Chasman DI, Rotter JI, Anderson CD, Zwart JA, Niiranen TJ, Fornage M, Liaw YP, Seshadri S, Fernández-Cadenas I, Walters RG, Ruff CT, Owolabi MO, Huffman JE, Milani L, Kamatani Y, Dichgans M, and Debette S

Subjects
Humans, Brain Ischemia genetics, Genome-Wide Association Study, Molecular Targeted Therapy, Multifactorial Inheritance, Europe ethnology, Asia, Eastern ethnology, Africa ethnology, Drug Discovery, Genetic Predisposition to Disease genetics, Ischemic Stroke genetics
Abstract

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry 1,2 . 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 analysis 3 , 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 approach 4 , 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 ancestry 5 . 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., (© 2022. The Author(s).)

Published
2022
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19. Genetic landscape of Gullah African Americans.

Author

Zimmerman KD, Schurr TG, Chen WM, Nayak U, Mychaleckyj JC, Quet Q, Moultrie LH, Divers J, Keene KL, Kamen DL, Gilkeson GS, Hunt KJ, Spruill IJ, Fernandes JK, Aldrich MC, Reich D, Garvey WT, Langefeld CD, Sale MM, and Ramos PS

Subjects
Africa, Europe, Genotype, Humans, Male, Black or African American genetics, Black People genetics
Abstract

Objectives: Gullah African Americans are descendants of formerly enslaved Africans living in the Sea Islands along the coast of the southeastern U.S., from North Carolina to Florida. Their relatively high numbers and geographic isolation were conducive to the development and preservation of a unique culture that retains deep African features. Although historical evidence supports a West-Central African ancestry for the Gullah, linguistic and cultural evidence of a connection to Sierra Leone has led to the suggestion of this country/region as their ancestral home. This study sought to elucidate the genetic structure and ancestry of the Gullah., Materials and Methods: We leveraged whole-genome genotype data from Gullah, African Americans from Jackson, Mississippi, African populations from Sierra Leone, and population reference panels from Africa and Europe to infer population structure, ancestry proportions, and global estimates of admixture., Results: Relative to non-Gullah African Americans from the Southeast US, the Gullah exhibited higher mean African ancestry, lower European admixture, a similarly small Native American contribution, and increased male-biased European admixture. A slightly tighter bottleneck in the Gullah 13 generations ago suggests a largely shared demographic history with non-Gullah African Americans. Despite a slightly higher relatedness to populations from Sierra Leone, our data demonstrate that the Gullah are genetically related to many West African populations., Discussion: This study confirms that subtle differences in African American population structure exist at finer regional levels. Such observations can help to inform medical genetics research in African Americans, and guide the interpretation of genetic data used by African Americans seeking to explore ancestral identities., (© 2021 The Authors. American Journal of Physical Anthropology published by Wiley Periodicals LLC.)

Published
2021
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20. Metabolic Traits and Stroke Risk in Individuals of African Ancestry: Mendelian Randomization Analysis.

Author

Fatumo S, Karhunen V, Chikowore T, Sounkou T, Udosen B, Ezenwa C, Nakabuye M, Soremekun O, Daghlas I, Ryan DK, Taylor A, Mason AM, Damrauer SM, Vujkovic M, Keene KL, Fornage M, Järvelin MR, Burgess S, and Gill D

Subjects
Adult, Cholesterol, HDL blood, Cholesterol, HDL genetics, Cholesterol, LDL blood, Cholesterol, LDL genetics, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 epidemiology, Diabetes Mellitus, Type 2 genetics, Female, Genetic Predisposition to Disease epidemiology, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Humans, Male, Middle Aged, Risk Factors, Stroke epidemiology, Triglycerides blood, Triglycerides genetics, United Kingdom epidemiology, Black People genetics, Mendelian Randomization Analysis methods, Stroke blood, Stroke genetics
Abstract

Background and Purpose: Metabolic traits affect ischemic stroke (IS) risk, but the degree to which this varies across different ethnic ancestries is not known. Our aim was to apply Mendelian randomization to investigate the causal effects of type 2 diabetes (T2D) liability and lipid traits on IS risk in African ancestry individuals, and to compare them to estimates obtained in European ancestry individuals., Methods: For African ancestry individuals, genetic proxies for T2D liability and circulating lipids were obtained from a meta-analysis of the African Partnership for Chronic Disease Research study, the UK Biobank, and the Million Veteran Program (total N=77 061). Genetic association estimates for IS risk were obtained from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (3734 cases and 18 317 controls). For European ancestry individuals, genetic proxies for the same metabolic traits were obtained from Million Veteran Program (lipids N=297 626, T2D N=148 726 cases, and 965 732 controls), and genetic association estimates for IS risk were obtained from the MEGASTROKE study (34 217 cases and 406 111 controls). Random-effects inverse-variance weighted Mendelian randomization was used as the main method, complemented with sensitivity analyses more robust to pleiotropy., Results: Higher genetically proxied T2D liability, LDL-C (low-density lipoprotein cholesterol), total cholesterol and lower genetically proxied HDL-C (high-density lipoprotein cholesterol) were associated with increased risk of IS in African ancestry individuals (odds ratio per doubling the odds of T2D liability [95% CI], 1.09 [1.07-1.11]; per standard-deviation increase in LDL-C, 1.12 [1.04-1.21]; total cholesterol: 1.23 [1.06-1.43]; HDL-C, 0.93 [0.89-0.99]). There was no evidence for differences in these estimates when performing analyses in European ancestry individuals., Conclusions: Our analyses support a causal effect of T2D liability and lipid traits on IS risk in African ancestry individuals, with Mendelian randomization estimates similar to those obtained in European ancestry individuals.

Published
2021
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21. DNA methylation analyses identify an intronic ZDHHC6 locus associated with time to recurrent stroke in the Vitamin Intervention for Stroke Prevention (VISP) clinical trial.

Author

Davis Armstrong NM, Chen WM, Hsu FC, Brewer MS, Cullell N, Fernández-Cadenas I, Williams SR, Sale MM, Worrall BB, and Keene KL

Subjects
Aged, Epigenome genetics, Female, Humans, Male, Middle Aged, Vitamins therapeutic use, Acyltransferases genetics, DNA Methylation genetics, Stroke genetics, Stroke prevention & control
Abstract

Aberrant DNA methylation profiles have been implicated in numerous cardiovascular diseases; however, few studies have investigated how these epigenetic modifications contribute to stroke recurrence. The aim of this study was to identify methylation loci associated with the time to recurrent cerebro- and cardiovascular events in individuals of European and African descent. DNA methylation profiles were generated for 180 individuals from the Vitamin Intervention for Stroke Prevention clinical trial using Illumina HumanMethylation 450K BeadChip microarrays, resulting in beta values for 470,871 autosomal CpG sites. Ethnicity-stratified survival analyses were performed using Cox Proportional Hazards regression models for associations between each methylation locus and the time to recurrent stroke or composite vascular event. Results were validated in the Vall d'Hebron University Hospital cohort from Barcelona, Spain. Network analyses of the methylation loci were generated using weighted gene coexpression network analysis. Primary analysis identified four significant loci, cg04059318, ch.2.81927627R, cg03584380, and cg24875416, associated with time to recurrent stroke. Secondary analysis identified three loci, cg00076998, cg16758041, and cg02365967, associated with time to composite vascular endpoint. Locus cg03584380, which is located in an intron of ZDHHC6, was replicated in the Vall d'Hebron University Hospital cohort. The results from this study implicate the degree of methylation at cg03584380 is associated with the time of recurrence for stroke or composite vascular events across two ethnically diverse groups. Furthermore, modules of loci were associated with clinical traits and blood biomarkers including previous number of strokes, prothrombin fragments 1 + 2, thrombomodulin, thrombin-antithrombin complex, triglyceride levels, and tissue plasminogen activator. Ultimately, these loci could serve as potential epigenetic biomarkers that could identify at-risk individuals in recurrence-prone populations., Competing Interests: The authors have declared that no competing interests exist.

Published
2021
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22. The Impact of COVID-19 on Racial-Ethnic Health Disparities in the US: Now Is the Time To Address the Problem.

Author

Ellis C, Jacobs M, Keene KL, and Grubaugh AL

Subjects
Black or African American, Humans, SARS-CoV-2, United States epidemiology, COVID-19 ethnology, COVID-19 prevention & control, Health Status Disparities, Healthcare Disparities ethnology, Healthcare Disparities standards, Minority Health standards, Quality Improvement organization & administration, Social Determinants of Health ethnology, Social Determinants of Health standards
Published
2021
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23. Multi-omic analysis of stroke recurrence in African Americans from the Vitamin Intervention for Stroke Prevention (VISP) clinical trial.

Author

Davis Armstrong NM, Spragley KJ, Chen WM, Hsu FC, Brewer MS, Horn PJ, Williams SR, Sale MM, Worrall BB, and Keene KL

Subjects
Aged, Female, Humans, Male, Middle Aged, Black or African American genetics, DNA Methylation drug effects, Genetic Loci, Genetic Variation, Metabolomics, Stroke blood, Stroke ethnology, Stroke genetics, Stroke prevention & control, Vitamins administration & dosage
Abstract

African Americans endure a nearly two-fold greater risk of suffering a stroke and are 2-3 times more likely to die from stroke compared to those of European ancestry. African Americans also have a greater risk of recurrent stroke and vascular events, which are deadlier and more disabling than incident stroke. Stroke is a multifactorial disease with both heritable and environmental risk factors. We conducted an integrative, multi-omic study on 922 plasma metabolites, 473,864 DNA methylation loci, and 556 variants from 50 African American participants of the Vitamin Intervention for Stroke Prevention clinical trial to help elucidate biomarkers contributing to recurrent stroke rates in this high risk population. Sixteen metabolites, including cotinine, N-delta-acetylornithine, and sphingomyelin (d17:1/24:1) were identified in t-tests of recurrent stroke outcome or baseline smoking status. Serum tricosanoyl sphingomyelin (d18:1/23:0) levels were significantly associated with recurrent stroke after adjusting for covariates in Cox Proportional Hazards models. Weighted Gene Co-expression Network Analysis identified moderate correlations between sphingolipid markers and clinical traits including days to recurrent stroke. Integrative analyses between genetic variants in sphingolipid pathway genes identified 29 nominal associations with metabolite levels in a one-way analysis of variance, while epigenomic analyses identified xenobiotics, predominately smoking-associated metabolites and pharmaceutical drugs, associated with methylation profiles. Taken together, our results suggest that metabolites, specifically those associated with sphingolipid metabolism, are potential plasma biomarkers for stroke recurrence in African Americans. Furthermore, genetic variation and DNA methylation may play a role in the regulation of these metabolites., Competing Interests: The authors have declared that no competing interests exist.

Published
2021
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24. Genome-Wide Association Study Meta-Analysis of Stroke in 22 000 Individuals of African Descent Identifies Novel Associations With Stroke.

Author

Keene KL, Hyacinth HI, Bis JC, Kittner SJ, Mitchell BD, Cheng YC, Pare G, Chong M, O'Donnell M, Meschia JF, Chen WM, Sale MM, Rich SS, Nalls MA, Zonderman AB, Evans MK, Wilson JG, Correa A, Markus HS, Traylor M, Lewis CM, Carty CL, Reiner A, Haessler J, Langefeld CD, Gottesman R, Mosley TH, Woo D, Yaffe K, Liu Y, Longstreth WT, Psaty BM, Kooperberg C, Lange LA, Sacco R, Rundek T, Lee JM, Cruchaga C, Furie KL, Arnett DK, Benavente OR, Grewal RP, Peddareddygari LR, Dichgans M, Malik R, Worrall BB, and Fornage M

Subjects
Black or African American ethnology, Cohort Studies, Genetic Predisposition to Disease ethnology, Humans, Stroke ethnology, Black or African American genetics, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Polymorphism, Single Nucleotide genetics, Stroke genetics
Abstract

Background and Purpose: Stroke is a complex disease with multiple genetic and environmental risk factors. Blacks endure a nearly 2-fold greater risk of stroke and are 2× to 3× more likely to die from stroke than European Americans., Methods: The COMPASS (Consortium of Minority Population Genome-Wide Association Studies of Stroke) has conducted a genome-wide association meta-analysis of stroke in >22 000 individuals of African ancestry (3734 cases, 18 317 controls) from 13 cohorts., Results: In meta-analyses, we identified one single nucleotide polymorphism (rs55931441) near the HNF1A gene that reached genome-wide significance ( P =4.62×10 -8 ) and an additional 29 variants with suggestive evidence of association ( P <1×10 -6 ), representing 24 unique loci. For validation, a look-up analysis for a 100 kb region flanking the COMPASS single nucleotide polymorphism was performed in SiGN (Stroke Genetics Network) Europeans, SiGN Hispanics, and METASTROKE (Europeans). Using a stringent Bonferroni correction P value of 2.08×10 -3 (0.05/24 unique loci), we were able to validate associations at the HNF1A locus in both SiGN ( P =8.18×10 -4 ) and METASTROKE ( P =1.72×10 -3 ) European populations. Overall, 16 of 24 loci showed evidence for validation across multiple populations. Previous studies have reported associations between variants in the HNF1A gene and lipids, C-reactive protein, and risk of coronary artery disease and stroke. Suggestive associations with variants in the SFXN4 and TMEM108 genes represent potential novel ischemic stroke loci., Conclusions: These findings represent the most thorough investigation of genetic determinants of stroke in individuals of African descent, to date.

Published
2020
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25. Differential expression of PHACTR1 in atheromatous versus normal carotid artery tissue.

Author

Green IE, Williams SR, Sale MM, Keene KL, Worrall BB, and Southerland AM

Subjects
Atherosclerosis, Coronary Artery Disease, Gene Expression, Humans, Male, Middle Aged, Carotid Arteries metabolism, Carotid Artery Diseases metabolism, Microfilament Proteins metabolism, Plaque, Atherosclerotic metabolism
Abstract

Variation in the phosphatase and actin regulator-1 (PHACTR1) gene, a downstream regulator of the endothelin-1 (EDN1) gene, has been implicated in the pathogenesis of several related vascular phenotypes including atherosclerotic coronary artery disease, non-atherosclerotic coronary artery dissection, and carotid artery dissection, though it has not been studied in carotid atherosclerosis. We analyzed differential expression of PHACTR1 and EDN1 between atheromatous and non-atheromatous carotid artery tissue within the same individual and found lower levels of PHACTR1 expression in the atheromatous carotid tissue., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Published
2020
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26. Publisher Correction: Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.

Author

Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese AK, van der Laan SW, Gretarsdottir S, Anderson CD, Chong M, Adams HHH, Ago T, Almgren P, Amouyel P, Ay H, Bartz TM, Benavente OR, Bevan S, Boncoraglio GB, Brown RD Jr, Butterworth AS, Carrera C, Carty CL, Chasman DI, Chen WM, Cole JW, Correa A, Cotlarciuc I, Cruchaga C, Danesh J, de Bakker PIW, DeStefano AL, den Hoed M, Duan Q, Engelter ST, Falcone GJ, Gottesman RF, Grewal RP, Gudnason V, Gustafsson S, Haessler J, Harris TB, Hassan A, Havulinna AS, Heckbert SR, Holliday EG, Howard G, Hsu FC, Hyacinth HI, Ikram MA, Ingelsson E, Irvin MR, Jian X, Jiménez-Conde J, Johnson JA, Jukema JW, Kanai M, Keene KL, Kissela BM, Kleindorfer DO, Kooperberg C, Kubo M, Lange LA, Langefeld CD, Langenberg C, Launer LJ, Lee JM, Lemmens R, Leys D, Lewis CM, Lin WY, Lindgren AG, Lorentzen E, Magnusson PK, Maguire J, Manichaikul A, McArdle PF, Meschia JF, Mitchell BD, Mosley TH, Nalls MA, Ninomiya T, O'Donnell MJ, Psaty BM, Pulit SL, Rannikmäe K, Reiner AP, Rexrode KM, Rice K, Rich SS, Ridker PM, Rost NS, Rothwell PM, Rotter JI, Rundek T, Sacco RL, Sakaue S, Sale MM, Salomaa V, Sapkota BR, Schmidt R, Schmidt CO, Schminke U, Sharma P, Slowik A, Sudlow CLM, Tanislav C, Tatlisumak T, Taylor KD, Thijs VNS, Thorleifsson G, Thorsteinsdottir U, Tiedt S, Trompet S, Tzourio C, van Duijn CM, Walters M, Wareham NJ, Wassertheil-Smoller S, Wilson JG, Wiggins KL, Yang Q, Yusuf S, Bis JC, Pastinen T, Ruusalepp A, Schadt EE, Koplev S, Björkegren JLM, Codoni V, Civelek M, Smith NL, Trégouët DA, Christophersen IE, Roselli C, Lubitz SA, Ellinor PT, Tai ES, Kooner JS, Kato N, He J, van der Harst P, Elliott P, Chambers JC, Takeuchi F, Johnson AD, Sanghera DK, Melander O, Jern C, Strbian D, Fernandez-Cadenas I, Longstreth WT Jr, Rolfs A, Hata J, Woo D, Rosand J, Pare G, Hopewell JC, Saleheen D, Stefansson K, Worrall BB, Kittner SJ, Seshadri S, Fornage M, Markus HS, Howson JMM, Kamatani Y, Debette S, and Dichgans M

Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019
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27. Epigenome-Wide Analyses Identify Two Novel Associations With Recurrent Stroke in the Vitamin Intervention for Stroke Prevention Clinical Trial.

Author

Davis Armstrong NM, Chen WM, Brewer MS, Williams SR, Sale MM, Worrall BB, and Keene KL

Abstract

DNA methylation, a well-characterized epigenetic modification that is influenced by both environment and genetic variation, has previously been implicated in a number of complex diseases, including cardiovascular disease and stroke. The goal of this study was to evaluate epigenome-wide associations with recurrent stroke and the folate one-carbon metabolism-related trait, plasma homocysteine (hcy). Differential methylation analyses were performed on 473,864 autosomal CpG loci, using Illumina HumanMethylation 450K array data in 180 ischemic stroke cases from the Vitamin Intervention for Stroke Prevention (VISP) clinical trial. Linear regression was used to assess associations between number of strokes prior to VISP enrollment and measures of hcy with degree of methylation (β-values), while logistic regression was used to evaluate recurrent stroke status and incident recurrent stroke associations. All regression analyses were stratified by race. Two differentially methylated CpG sites exceeded epigenome-wide significance ( p ≤ 1.055 × 10 -7 ) for prior number of strokes (PNS) in European Americans. The top locus, cg22812874, was located in the ankyrin repeat and SOCS box containing 10 gene ( ASB10 ; p = 3.4 × 10 -9 ; β = -0.0308; 95% CI = -0.040, -0.002). Methylation locus cg00340919, located in an intron of the tetratricopeptide repeat domain 37 gene, was also statistically significant ( TTC37 ; p = 8.74 × 10 -8 ; β = -0.0517; 95% CI = -0.069, -0.034). An additional 138 CpG sites met our threshold for suggestive significance ( p ≤ 5 × 10 -5 ). We evaluated DNA methylation associated with recurrent stroke and hcy phenotypes across the epigenome. Hypermethylation at two CpG sites located in ASB10 and TTC37 was associated with fewer strokes prior to VISP enrollment. Our findings present a foundation for additional epigenome-wide studies, as well as mechanistic studies into epigenetic marks that influence recurrent stroke risk.

Published
2018
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28. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.

Author

Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese AK, van der Laan SW, Gretarsdottir S, Anderson CD, Chong M, Adams HHH, Ago T, Almgren P, Amouyel P, Ay H, Bartz TM, Benavente OR, Bevan S, Boncoraglio GB, Brown RD Jr, Butterworth AS, Carrera C, Carty CL, Chasman DI, Chen WM, Cole JW, Correa A, Cotlarciuc I, Cruchaga C, Danesh J, de Bakker PIW, DeStefano AL, den Hoed M, Duan Q, Engelter ST, Falcone GJ, Gottesman RF, Grewal RP, Gudnason V, Gustafsson S, Haessler J, Harris TB, Hassan A, Havulinna AS, Heckbert SR, Holliday EG, Howard G, Hsu FC, Hyacinth HI, Ikram MA, Ingelsson E, Irvin MR, Jian X, Jiménez-Conde J, Johnson JA, Jukema JW, Kanai M, Keene KL, Kissela BM, Kleindorfer DO, Kooperberg C, Kubo M, Lange LA, Langefeld CD, Langenberg C, Launer LJ, Lee JM, Lemmens R, Leys D, Lewis CM, Lin WY, Lindgren AG, Lorentzen E, Magnusson PK, Maguire J, Manichaikul A, McArdle PF, Meschia JF, Mitchell BD, Mosley TH, Nalls MA, Ninomiya T, O'Donnell MJ, Psaty BM, Pulit SL, Rannikmäe K, Reiner AP, Rexrode KM, Rice K, Rich SS, Ridker PM, Rost NS, Rothwell PM, Rotter JI, Rundek T, Sacco RL, Sakaue S, Sale MM, Salomaa V, Sapkota BR, Schmidt R, Schmidt CO, Schminke U, Sharma P, Slowik A, Sudlow CLM, Tanislav C, Tatlisumak T, Taylor KD, Thijs VNS, Thorleifsson G, Thorsteinsdottir U, Tiedt S, Trompet S, Tzourio C, van Duijn CM, Walters M, Wareham NJ, Wassertheil-Smoller S, Wilson JG, Wiggins KL, Yang Q, Yusuf S, Bis JC, Pastinen T, Ruusalepp A, Schadt EE, Koplev S, Björkegren JLM, Codoni V, Civelek M, Smith NL, Trégouët DA, Christophersen IE, Roselli C, Lubitz SA, Ellinor PT, Tai ES, Kooner JS, Kato N, He J, van der Harst P, Elliott P, Chambers JC, Takeuchi F, Johnson AD, Sanghera DK, Melander O, Jern C, Strbian D, Fernandez-Cadenas I, Longstreth WT Jr, Rolfs A, Hata J, Woo D, Rosand J, Pare G, Hopewell JC, Saleheen D, Stefansson K, Worrall BB, Kittner SJ, Seshadri S, Fornage M, Markus HS, Howson JMM, Kamatani Y, Debette S, and Dichgans M

Subjects
Computational Biology, Databases, Genetic, Epigenesis, Genetic, Female, Gene Regulatory Networks, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, INDEL Mutation, Linkage Disequilibrium, Male, Models, Genetic, Polymorphism, Single Nucleotide, Risk Factors, Stroke classification, Stroke physiopathology, Stroke genetics
Abstract

Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.

Published
2018
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29. Cervical Artery Dissection in Patients of African Ancestry.

Author

Green IE, Rahman SA, Owens DL, Sale MM, Currie LJ, Keene KL, Worrall BB, and Southerland AM

Subjects
Adult, Comorbidity, Databases, Factual, Female, Gene Frequency, Gene-Environment Interaction, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Phenotype, Prevalence, Risk Assessment, Risk Factors, Stroke diagnosis, Vertebral Artery Dissection diagnosis, Virginia epidemiology, Black or African American, Black People genetics, Cervical Vertebrae blood supply, Microfilament Proteins genetics, Polymorphism, Single Nucleotide, Stroke ethnology, Stroke genetics, Vertebral Artery Dissection ethnology, Vertebral Artery Dissection genetics, White People genetics
Abstract

Background and Purpose: The majority of published data in cervical artery dissection (CeAD), a common cause of stroke in young adults, derive from populations of European ancestry (EA), including a recent genome-wide study identifying an association with the rs9349379 polymorphism of the PHACTR1 gene. Little is known about CeAD in individuals of African ancestry (AA) despite robust epidemiological data showing increased risk of stroke at younger ages. We hypothesize that AA patients with CeAD have different epidemiology and clinical profiles compared to those of EA, and a different genetic architecture related to rs9349379 of the PHACTR1 gene., Methods: We searched a single-center database of CeAD to identify AA and EA patients. We compared differential prevalence of CeAD versus all young stroke between AA and EA patients. We characterized clinical profiles via electronic medical record review. Data include descriptive statistics reported as medians or percentages. We also obtained publicly available allele frequencies of rs9349379 in AA and EA populations., Results: AA patients comprise 7% of CeAD cases and 27% of young stroke cases while EA patients comprise 90% of CeAD cases and 70% of young stroke cases. Prevalence of hypertension, diabetes mellitus, and hyperlipidemia were 74, 30, and 50%, respectively, in AA patients compared to 37, 6, and 25% in EA patients. Allele frequencies for the CeAD risk allele, rs9349379(A), are higher in AA populations compared to EA populations., Conclusion: AA patients represent a smaller proportion of CeAD cases compared to young stroke cases at our center. AA patients suffering CeAD have higher prevalence of both vascular risk factors and frequency of the CeAD risk allele compared to EA patients. These findings suggest a complex interplay between traditional vascular risk factors and genetic predisposition underlying CeAD pathogenesis. Further prospective research is needed to clarify these associations and disparities., (© 2018 S. Karger AG, Basel.)

Published
2018
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30. Genetic Drivers of von Willebrand Factor Levels in an Ischemic Stroke Population and Association With Risk for Recurrent Stroke.

Author

Williams SR, Hsu FC, Keene KL, Chen WM, Dzhivhuho G, Rowles JL 3rd, Southerland AM, Furie KL, Rich SS, Worrall BB, and Sale MM

Subjects
Aged, Aged, 80 and over, Brain Ischemia genetics, Female, Gene Expression, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Recurrence, Risk, Stroke genetics, von Willebrand Factor genetics, Brain Ischemia blood, Quantitative Trait Loci genetics, Stroke blood, von Willebrand Factor metabolism
Abstract

Background and Purpose: von Willebrand factor (vWF) plays an important role in thrombus formation during cerebrovascular damage. We sought to investigate the potential role of circulating vWF in recurrent cerebrovascular events and identify genetic contributors to variation in vWF level in an ischemic stroke population., Methods: We analyzed the effect of circulating vWF on risk of recurrent stroke using survival models in the VISP trial (Vitamin Intervention for Stroke Prevention) and the use of vWF in reclassification over traditional factors. We conducted a genome-wide association study) with imputation, based on 1000 Genomes Project data, for circulating vWF levels and then interrogated loci previously associated with vWF levels. We performed expression quantitative trait locus analysis for vWF across different tissues., Results: Elevated vWF levels were associated with increased risk for recurrent stroke in VISP. Adding vWF to traditional clinical parameters also improved recurrent stroke risk prediction. We identified single-nucleotide polymorphisms significantly associated with circulating vWF at the ABO locus ( P <5×10 -8 ) and replicated findings from previous genetic associations of vWF levels in humans. Expression quantitative trait locus analyses demonstrate that most associated ABO single-nucleotide polymorphisms were also associated with vWF gene expression., Conclusions: Elevated vWF levels are associated with recurrent stroke in VISP. In the VISP population, genetic determinants of vWF levels that impact vWF gene expression were identified. These data add to our knowledge of the pathophysiologic and genetic basis for recurrent stroke risk and may have implications for clinical care decision making., (© 2017 American Heart Association, Inc.)

Published
2017
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31. Shared genetic susceptibility of vascular-related biomarkers with ischemic and recurrent stroke.

Author

Williams SR, Hsu FC, Keene KL, Chen WM, Nelson S, Southerland AM, Madden EB, Coull B, Gogarten SM, Furie KL, Dzhivhuho G, Rowles JL, Mehndiratta P, Malik R, Dupuis J, Lin H, Seshadri S, Rich SS, Sale MM, and Worrall BB

Subjects
Aged, Brain Ischemia genetics, C-Reactive Protein genetics, Female, Fibrinogen genetics, Fibrinogen metabolism, Gene Expression, Genetic Loci, Humans, Male, Middle Aged, Oxidoreductases genetics, Polymorphism, Single Nucleotide, Randomized Controlled Trials as Topic, Recurrence, Stroke genetics, Biomarkers, Brain Ischemia metabolism, C-Reactive Protein metabolism, Genetic Predisposition to Disease, Genome-Wide Association Study, Stroke metabolism
Abstract

Objective: To investigate the genetic contributors to cerebrovascular disease and variation in biomarkers of ischemic stroke., Methods: The Vitamin Intervention for Stroke Prevention Trial (VISP) was a randomized, controlled clinical trial of B vitamin supplementation to prevent recurrent stroke, myocardial infarction, or death. VISP collected baseline measures of C-reactive protein (CRP), fibrinogen, creatinine, prothrombin fragments F1+2, thrombin-antithrombin complex, and thrombomodulin prior to treatment initiation. Genome-wide association scans were conducted for these traits and follow-up replication analyses were performed., Results: We detected an association between CRP single nucleotide polymorphisms (SNPs) and circulating CRP levels (most associated SNP, rs2592902, p = 1.14 × 10(-9)) in 2,100 VISP participants. We discovered a novel association for CRP level in the AKR1D1 locus (rs2589998, p = 7.3 × 10(-8), approaching genome-wide significance) that also is an expression quantitative trait locus for CRP gene expression. We replicated previously identified associations of fibrinogen with SNPs in the FGB and LEPR loci. CRP-associated SNPs and CRP levels were significantly associated with risk of ischemic stroke and recurrent stroke in VISP as well as specific stroke subtypes in METASTROKE. Fibrinogen levels but not fibrinogen-associated SNPs were also found to be associated with recurrent stroke in VISP., Conclusions: Our data identify a genetic contribution to inflammatory and hemostatic biomarkers in a stroke population. Additionally, our results suggest shared genetic contributions to circulating CRP levels measured poststroke and risk for incident and recurrent ischemic stroke. These data broaden our understanding of genetic contributors to biomarker variation and ischemic stroke risk, which should be useful in clinical risk evaluation., (© 2015 American Academy of Neurology.)

Published
2016
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32. Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

Author

Pattaro C, Teumer A, Gorski M, Chu AY, Li M, Mijatovic V, Garnaas M, Tin A, Sorice R, Li Y, Taliun D, Olden M, Foster M, Yang Q, Chen MH, Pers TH, Johnson AD, Ko YA, Fuchsberger C, Tayo B, Nalls M, Feitosa MF, Isaacs A, Dehghan A, d'Adamo P, Adeyemo A, Dieffenbach AK, Zonderman AB, Nolte IM, van der Most PJ, Wright AF, Shuldiner AR, Morrison AC, Hofman A, Smith AV, Dreisbach AW, Franke A, Uitterlinden AG, Metspalu A, Tonjes A, Lupo A, Robino A, Johansson Å, Demirkan A, Kollerits B, Freedman BI, Ponte B, Oostra BA, Paulweber B, Krämer BK, Mitchell BD, Buckley BM, Peralta CA, Hayward C, Helmer C, Rotimi CN, Shaffer CM, Müller C, Sala C, van Duijn CM, Saint-Pierre A, Ackermann D, Shriner D, Ruggiero D, Toniolo D, Lu Y, Cusi D, Czamara D, Ellinghaus D, Siscovick DS, Ruderfer D, Gieger C, Grallert H, Rochtchina E, Atkinson EJ, Holliday EG, Boerwinkle E, Salvi E, Bottinger EP, Murgia F, Rivadeneira F, Ernst F, Kronenberg F, Hu FB, Navis GJ, Curhan GC, Ehret GB, Homuth G, Coassin S, Thun GA, Pistis G, Gambaro G, Malerba G, Montgomery GW, Eiriksdottir G, Jacobs G, Li G, Wichmann HE, Campbell H, Schmidt H, Wallaschofski H, Völzke H, Brenner H, Kroemer HK, Kramer H, Lin H, Leach IM, Ford I, Guessous I, Rudan I, Prokopenko I, Borecki I, Heid IM, Kolcic I, Persico I, Jukema JW, Wilson JF, Felix JF, Divers J, Lambert JC, Stafford JM, Gaspoz JM, Smith JA, Faul JD, Wang JJ, Ding J, Hirschhorn JN, Attia J, Whitfield JB, Chalmers J, Viikari J, Coresh J, Denny JC, Karjalainen J, Fernandes JK, Endlich K, Butterbach K, Keene KL, Lohman K, Portas L, Launer LJ, Lyytikäinen LP, Yengo L, Franke L, Ferrucci L, Rose LM, Kedenko L, Rao M, Struchalin M, Kleber ME, Cavalieri M, Haun M, Cornelis MC, Ciullo M, Pirastu M, de Andrade M, McEvoy MA, Woodward M, Adam M, Cocca M, Nauck M, Imboden M, Waldenberger M, Pruijm M, Metzger M, Stumvoll M, Evans MK, Sale MM, Kähönen M, Boban M, Bochud M, Rheinberger M, Verweij N, Bouatia-Naji N, Martin NG, Hastie N, Probst-Hensch N, Soranzo N, Devuyst O, Raitakari O, Gottesman O, Franco OH, Polasek O, Gasparini P, Munroe PB, Ridker PM, Mitchell P, Muntner P, Meisinger C, Smit JH, Kovacs P, Wild PS, Froguel P, Rettig R, Mägi R, Biffar R, Schmidt R, Middelberg RP, Carroll RJ, Penninx BW, Scott RJ, Katz R, Sedaghat S, Wild SH, Kardia SL, Ulivi S, Hwang SJ, Enroth S, Kloiber S, Trompet S, Stengel B, Hancock SJ, Turner ST, Rosas SE, Stracke S, Harris TB, Zeller T, Zemunik T, Lehtimäki T, Illig T, Aspelund T, Nikopensius T, Esko T, Tanaka T, Gyllensten U, Völker U, Emilsson V, Vitart V, Aalto V, Gudnason V, Chouraki V, Chen WM, Igl W, März W, Koenig W, Lieb W, Loos RJ, Liu Y, Snieder H, Pramstaller PP, Parsa A, O'Connell JR, Susztak K, Hamet P, Tremblay J, de Boer IH, Böger CA, Goessling W, Chasman DI, Köttgen A, Kao WH, and Fox CS

Subjects
Gene Expression Regulation, Genome-Wide Association Study, Genotype, Humans, Genetic Predisposition to Disease, Renal Insufficiency, Chronic genetics
Abstract

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways.

Published
2016
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33. Meta-Analysis of Genome-Wide Association Studies Identifies Genetic Risk Factors for Stroke in African Americans.

Author

Carty CL, Keene KL, Cheng YC, Meschia JF, Chen WM, Nalls M, Bis JC, Kittner SJ, Rich SS, Tajuddin S, Zonderman AB, Evans MK, Langefeld CD, Gottesman R, Mosley TH, Shahar E, Woo D, Yaffe K, Liu Y, Sale MM, Dichgans M, Malik R, Longstreth WT Jr, Mitchell BD, Psaty BM, Kooperberg C, Reiner A, Worrall BB, and Fornage M

Subjects
Case-Control Studies, Cohort Studies, Genetic Predisposition to Disease epidemiology, Humans, Polymorphism, Single Nucleotide genetics, Risk Factors, Stroke diagnosis, Stroke epidemiology, Black or African American genetics, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Stroke genetics
Abstract

Background and Purpose: The majority of genome-wide association studies (GWAS) of stroke have focused on European-ancestry populations; however, none has been conducted in African Americans, despite the disproportionately high burden of stroke in this population. The Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) was established to identify stroke susceptibility loci in minority populations., Methods: Using METAL, we conducted meta-analyses of GWAS in 14 746 African Americans (1365 ischemic and 1592 total stroke cases) from COMPASS, and tested genetic variants with P<10(-6) for validation in METASTROKE, a consortium of ischemic stroke genetic studies in European-ancestry populations. We also evaluated stroke loci previously identified in European-ancestry populations., Results: The 15q21.3 locus linked with lipid levels and hypertension was associated with total stroke (rs4471613; P=3.9×10(-8)) in African Americans. Nominal associations (P<10(-6)) for total or ischemic stroke were observed for 18 variants in or near genes implicated in cell cycle/mRNA presplicing (PTPRG, CDC5L), platelet function (HPS4), blood-brain barrier permeability (CLDN17), immune response (ELTD1, WDFY4, and IL1F10-IL1RN), and histone modification (HDAC9). Two of these loci achieved nominal significance in METASTROKE: 5q35.2 (P=0.03), and 1p31.1 (P=0.018). Four of 7 previously reported ischemic stroke loci (PITX2, HDAC9, CDKN2A/CDKN2B, and ZFHX3) were nominally associated (P<0.05) with stroke in COMPASS., Conclusions: We identified a novel genetic variant associated with total stroke in African Americans and found that ischemic stroke loci identified in European-ancestry populations may also be relevant for African Americans. Our findings support investigation of diverse populations to identify and characterize genetic risk factors, and the importance of shared genetic risk across populations., (© 2015 American Heart Association, Inc.)

Published
2015
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34. Fine mapping and functional studies of risk variants for type 1 diabetes at chromosome 16p13.13.

Author

Tomlinson MJ 4th, Pitsillides A, Pickin R, Mika M, Keene KL, Hou X, Mychaleckyj J, Chen WM, Concannon P, and Onengut-Gumuscu S

Subjects
Case-Control Studies, Chromosome Mapping, Genetic Predisposition to Disease, Humans, Polymorphism, Single Nucleotide, Reverse Transcriptase Polymerase Chain Reaction, Chromosomes, Human, Pair 16 genetics, DNA-Binding Proteins genetics, Diabetes Mellitus, Type 1 genetics, Lectins, C-Type genetics, Membrane Proteins genetics, Monosaccharide Transport Proteins genetics, RNA, Messenger analysis
Abstract

Single nucleotide polymorphisms (SNPs) located in the chromosomal region 16p13.13 have been previously associated with risk for several autoimmune diseases, including type 1 diabetes. To identify and localize specific risk variants for type 1 diabetes in this region and understand the mechanism of their action, we resequenced a 455-kb region in type 1 diabetic patients and unaffected control subjects, identifying 93 novel variants. A panel of 939 SNPs that included 46 of these novel variants was genotyped in 3,070 multiplex families with type 1 diabetes. Forty-eight SNPs, all located in CLEC16A, provided a statistically significant association (P < 5.32 × 10(-5)) with disease, with rs34306440 being most significantly associated (P = 5.74 × 10(-6)). The panel of SNPs used for fine mapping was also tested for association with transcript levels for each of the four genes in the region in B lymphoblastoid cell lines. Significant associations were observed only for transcript levels of DEXI, a gene with unknown function. We examined the relationship between the odds ratio for type 1 diabetes and the magnitude of the effect of DEXI transcript levels for each SNP in the region. Among SNPs significantly associated with type 1 diabetes, the common allele conferred an increased risk for disease and corresponded to lower DEXI expression. Our results suggest that the primary mechanism by which genetic variation at CLEC16A contributes to the risk for type 1 diabetes is through reduced expression of DEXI., (© 2014 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Published
2014
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