Differential ischemic stroke risk linked to novel subtypes of type 2 diabetes: insights from a Mendelian randomization analysis

D. Kuriakose, Z. Xiao, Pathophysiology and treatment of stroke: present status and future perspectives. Int. J. Mol. Sci. 21, 7609 (2020). https://doi.org/10.3390/ijms21207609

Article  CAS  PubMed  PubMed Central  Google Scholar 

E.S. Donkor, Stroke in the 21st century: a snapshot of the burden, epidemiology, and quality of life. Stroke Res. Treat. 2018, 3238165 (2018). https://doi.org/10.1155/2018/3238165

Article  PubMed  PubMed Central  Google Scholar 

H.S. Markus, Stroke genetics. Hum. Mol. Genet. 20, R124–131 (2011). https://doi.org/10.1093/hmg/ddr345

Article  CAS  PubMed  Google Scholar 

M. Traylor, M. Farrall, E.G. Holliday, C. Sudlow, J.C. Hopewell, Y.-C. Cheng, M. Fornage, M.A. Ikram, R. Malik, S. Bevan, U. Thorsteinsdottir, M.A. Nalls, W. Longstreth, K.L. Wiggins, S. Yadav, E.A. Parati, A.L. DeStefano, B.B. Worrall, S.J. Kittner, M.S. Khan, A.P. Reiner, A. Helgadottir, S. Achterberg, I. Fernandez-Cadenas, S. Abboud, R. Schmidt, M. Walters, W.-M. Chen, E.B. Ringelstein, M. O’Donnell, W.K. Ho, J. Pera, R. Lemmens, B. Norrving, P. Higgins, M. Benn, M. Sale, G. Kuhlenbäumer, A.S.F. Doney, A.M. Vicente, H. Delavaran, A. Algra, G. Davies, S.A. Oliveira, C.N.A. Palmer, I. Deary, H. Schmidt, M. Pandolfo, J. Montaner, C. Carty, P.I.W. de Bakker, K. Kostulas, J.M. Ferro, N.R. van Zuydam, E. Valdimarsson, B.G. Nordestgaard, A. Lindgren, V. Thijs, A. Slowik, D. Saleheen, G. Paré, K. Berger, G. Thorleifsson, A. Hofman, T.H. Mosley, B.D. Mitchell, K. Furie, R. Clarke, C. Levi, S. Seshadri, A. Gschwendtner, G.B. Boncoraglio, P. Sharma, J.C. Bis, S. Gretarsdottir, B.M. Psaty, P.M. Rothwell, J. Rosand, J.F. Meschia, K. Stefansson, M. Dichgans, H.S. Markus, Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a metaanalysis of genome-wide association studies. Lancet. Neurology. 11, 951–962 (2012). https://doi.org/10.1016/S1474-4422(12)70234-X

Article  PubMed  Google Scholar 

S.C. Larsson, A. Wallin, N. Håkansson, O. Stackelberg, M. Bäck, A. Wolk, Type 1 and type 2 diabetes mellitus and incidence of seven cardiovascular diseases. Int. J. Cardiol. 262, 66–70 (2018). https://doi.org/10.1016/j.ijcard.2018.03.099

Article  PubMed  Google Scholar 

S. Chatterjee, K. Khunti, M.J. Davies, Type 2 diabetes. Lancet 389, 2239–2251 (2017). https://doi.org/10.1016/S0140-6736(17)30058-2

Article  CAS  PubMed  Google Scholar 

A. Mahajan, J. Wessel, S.M. Willems, W. Zhao, N.R. Robertson, A.Y. Chu, W. Gan, H. Kitajima, D. Taliun, N.W. Rayner, X. Guo, Y. Lu, M. Li, R.A. Jensen, Y. Hu, S. Huo, K.K. Lohman, W. Zhang, J.P. Cook, B.P. Prins, J. Flannick, N. Grarup, V.V. Trubetskoy, J. Kravic, Y.J. Kim, D.V. Rybin, Yaghootkar, H. Müller-Nurasyid, M. Meidtner, K. Li-Gao, R. Varga, T.V. Marten, J. Li, J. Smith, A.V. An, P. Ligthart, S. Gustafsson, S. Malerba, G. Demirkan, A. Tajes, J.F. Steinthorsdottir, V. Wuttke, M. Lecoeur, C. Preuss, M. Bielak, L.F. Graff, M. Highland, H.M. Justice, A.E. Liu, D.J. Marouli, E. Peloso, G.M. Warren; H.R., ExomeBP Consortium, MAGIC Consortium, GIANT Consortium, Afaq, S., Afzal, S., Ahlqvist, E., Almgren, P., Amin, N., Bang, L.B., Bertoni, A.G., Bombieri, C., Bork-Jensen, J., Brandslund, I., Brody, J.A., Burtt, N.P., Canouil, M., Chen, Y.-D.I., Cho, Y.S., Christensen, C., Eastwood, S.V., Eckardt, K.-U., Fischer, K., Gambaro, G., Giedraitis, V., Grove, M.L., de Haan, H.G., Hackinger, S., Hai, Y., Han, S., Tybjærg-Hansen, A., Hivert, M.-F., Isomaa, B., Jäger, S., Jørgensen, M.E., Jørgensen, T., Käräjämäki, A., Kim, B.-J., Kim, S.S., Koistinen, H.A., Kovacs, P., Kriebel, J., Kronenberg, F., Läll, K., Lange, L.A., Lee, J.-J., Lehne, B., Li, H., Lin, K.-H., Linneberg, A., Liu, C.-T., Liu, J., Loh, M., Mägi, R., Mamakou, V., McKean-Cowdin, R., Nadkarni, G., Neville, M., Nielsen, S.F., Ntalla, I., Peyser, P.A., Rathmann, W., Rice, K., Rich, S.S., Rode, L., Rolandsson, O., Schönherr, S., Selvin, E., Small, K.S., Stančáková, A., Surendran, P., Taylor, K.D., Teslovich, T.M., Thorand, B., Thorleifsson, G., Tin, A., Tönjes, A., Varbo, A., Witte, D.R., Wood, A.R., Yajnik, P., Yao, J., Yengo, L., Young, R., Amouyel, P., Boeing, H., Boerwinkle, E., Bottinger, E.P., Chowdhury, R., Collins, F.S., Dedoussis, G., Dehghan, A., Deloukas, P., Ferrario, M.M., Ferrières, J., Florez, J.C., Frossard, P., Gudnason, V., Harris, T.B., Heckbert, S.R., Howson, J.M.M., Ingelsson, M., Kathiresan, S., Kee, F., Kuusisto, J., Langenberg, C., Launer, L.J., Lindgren, C.M., Männistö, S., Meitinger, T., Melander, O., Mohlke, K.L., Moitry, M., Morris, A.D., Murray, A.D., de Mutsert, R., Orho-Melander, M., Owen, K.R., Perola, M., Peters, A., Province, M.A., Rasheed, A., Ridker, P.M., Rivadineira, F., Rosendaal, F.R., Rosengren, A.H., Salomaa, V., Sheu, W.H.-H., Sladek, R., Smith, B.H., Strauch, K., Uitterlinden, A.G., Varma, R., Willer, C.J., Blüher, M., Butterworth, A.S., Chambers, J.C., Chasman, D.I., Danesh, J., van Duijn, C., Dupuis, J., Franco, O.H., Franks, P.W., Froguel, P., Grallert, H., Groop, L., Han, B.-G., Hansen, T., Hattersley, A.T., Hayward, C., Ingelsson, E., Kardia, S.L.R., Karpe, F., Kooner, J.S., Köttgen, A., Kuulasmaa, K., Laakso, M., Lin, X., Lind, L., Liu, Y., Loos, R.J.F., Marchini, J., Metspalu, A., Mook-Kanamori, D., Nordestgaard, B.G., Palmer, C.N.A., Pankow, J.S., Pedersen, O., Psaty, B.M., Rauramaa, R., Sattar, N., Schulze, M.B., Soranzo, N., Spector, T.D., Stefansson, K., Stumvoll, M., Thorsteinsdottir, U., Tuomi, T., Tuomilehto, J., Wareham, N.J., Wilson, J.G., Zeggini, E., Scott, R.A., Barroso, I., Frayling, T.M., Goodarzi, M.O., Meigs, J.B., Boehnke, M., Saleheen, D., Morris, A.P., Rotter, J.I., McCarthy, M.I., Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat. Genet. 50, 559–571 (2018). https://doi.org/10.1038/s41588-018-0084-1

Article  CAS  PubMed  PubMed Central  Google Scholar 

P.W. Franks, M.I. McCarthy, Exposing the exposures responsible for type 2 diabetes and obesity. Science 354, 69–73 (2016). https://doi.org/10.1126/science.aaf5094

Article  CAS  PubMed  Google Scholar 

E. Ahlqvist, R.B. Prasad, L. Groop, 100 YEARS OF INSULIN: Towards improved precision and a new classification of diabetes mellitus. J. Endocrinol. 252, R59–R70 (2022). https://doi.org/10.1530/JOE-20-0596

Article  CAS  Google Scholar 

American Diabetes Association: 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021. Diabetes Care. 44, S15–S33 (2021). https://doi.org/10.2337/dc21-S002.

T. Tuomi, N. Santoro, S. Caprio, M. Cai, J. Weng, L. Groop, The many faces of diabetes: a disease with increasing heterogeneity. Lancet. 383, 1084–1094 (2014). https://doi.org/10.1016/S0140-6736(13)62219-9

Article  PubMed  Google Scholar 

E. Ahlqvist, P. Storm, A. Käräjämäki, M. Martinell, M. Dorkhan, A. Carlsson, P. Vikman, R.B. Prasad, D.M. Aly, P. Almgren, Y. Wessman, N. Shaat, P. Spégel, H. Mulder, E. Lindholm, O. Melander, O. Hansson, U. Malmqvist, Å. Lernmark, K. Lahti, T. Forsén, T. Tuomi, A.H. Rosengren, L. Groop, Novel subgroups of adultonset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 6, 361–369 (2018). https://doi.org/10.1016/S2213-8587(18)30051-2

Article  PubMed  Google Scholar 

H. Tanabe, H. Saito, A. Kudo, N. Machii, H. Hirai, G. Maimaituxun, K. Tanaka, H. Masuzaki, T. Watanabe, K. Asahi, J. Kazama, M. Shimabukuro,, Factors associated with risk of diabetic complications in novel cluster-based diabetes subgroups: a japanese retrospective cohort study. J. Clinical Medicine 9, 2083 (2020). https://doi.org/10.3390/jcm9072083

Article  Google Scholar 

X. Zou, X. Zhou, Z. Zhu, L. Ji, Novel subgroups of patients with adult-onset diabetes in Chinese and US populations. Lancet Diabetes Endocrinol. 7, 9–11 (2019). https://doi.org/10.1016/S2213-8587(18)30316-4

Article  PubMed  Google Scholar 

E. Sanderson, M.M. Glymour, M.V. Holmes, H. Kang, J. Morrison, M.R. Munafò, T. Palmer, C.M. Schooling, C. Wallace, Q. Zhao, G. Davey Smith, Mendelian randomization. Nat. Rev. Methods Primers. 2, 1–21 (2022). https://doi.org/10.1038/s43586-021-00092-5

Article  CAS  Google Scholar 

V.W. Skrivankova, R.C. Richmond, B.A.R. Woolf, N.M. Davies, S.A. Swanson, T.J. VanderWeele, N.J. Timpson, J.P.T. Higgins, N. Dimou, C. Langenberg, E.W. Loder, R.M. Golub, M. Egger, G. Davey Smith, J.B. Richards, Strengthening the reporting of observational studies in epidemiology using mendelian randomization (STROBE-MR): explanation and elaboration. BMJ 375, n2233 (2021). https://doi.org/10.1136/bmj.n2233

Article  PubMed  PubMed Central  Google Scholar 

R. Malik, G. Chauhan, M. Traylor, M. Sargurupremraj, Y. Okada, A. Mishra, L. Rutten-Jacobs, A.-K. Giese, S.W. van der Laan, S. Gretarsdottir, C.D. Anderson, M. Chong, H.H.H. Adams, T. Ago, P. Almgren, P. Amouyel, H. Ay, T.M. Bartz, O.R. Benavente, S. Bevan, G.B. Boncoraglio, R.D. Brown, A.S. Butterworth, C. Carrera, C.L. Carty, D.I. Chasman, W.-M. Chen, J.W. Cole, A. Correa, I. Cotlarciuc, C. Cruchaga, J. Danesh, P.I.W. de Bakker, A.L. DeStefano, M. den Hoed, Q. Duan, S.T. Engelter, G.J. Falcone, R.F. Gottesman, R.P. Grewal, V. Gudnason, S. Gustafsson, J. Haessler, T.B. Harris, A. Hassan, A.S. Havulinna, S.R. Heckbert, E.G. Holliday, G. Howard, F.-C. Hsu, H.I. Hyacinth, M.A. Ikram, E. ingelsson, M.R. Irvin, X. Jian, J. Jimenez-Conde, J.A. Johnson, J.W. Jukema, M. Kanai, K.L. Keene, B.M. Kissela, D.O. Kleindorfer, C. Kooperberg, M. Kubo, L.A. Lange, C.D. Langefeld, C. Langenberg, L.J. Launer, J.-M. Lee, R. Lemmens, D. Leys, C.M. Lewis, W.-Y. Lin, A.G. Lindgren, E. Lorentzen, P.K. Magnusson, J. Maguire, A. Manichaikul, P.F. McArdle, J.F. Meschia, B.D. Mitchell, T.H. Mosley, M.A. Nalls, T. Ninomiya, M.J. O’Donnell, B.M. Psaty, S.L. Pulit, K. Rannikmäe, A.P. Reiner, K.M. Rexrode, K. Rice, S.S. Rich, P.M. Ridker, N.S. Rost, P.M. Rothwell, J.I. Rotter, T. Rundek, R.L. Sacco, S. Sakaue, M.M. Sale, V. Salomaa, B.R. Sapkota, R. Schmidt, C.O. Schmidt, U. Schminke, P. Sharma, A. Slowik, C.L.M. Sudlow, C. Tanislav, T. Tatlisumak, K.D. Taylor, V.N.S. Thijs, G. Thorleifsson, U. Thorsteinsdottir, S. Tiedt, S. Trompet, C. Tzourio, C.M. van Duijn, M. Walters, N.J. Wareham, S. Wassertheil-Smoller, J.G. Wilson, K.L. Wiggins, Q. Yang, S. Yusuf, J.C. Bis, T. Pastinen, A. Ruusalepp, E.E. Schadt, S. Koplev, J.L.M. Björkegren, V. Codoni, M. Civelek, N.L. Smith, D.A. Tregouet, I.E. Christophersen, C. Roselli, S.A. Lubitz, P.T. Ellinor, E.S. Tai, J.S. Kooner, N. Kato, J. He, P. van der Harst, P. Elliott, J.C. Chambers, F. Takeuchi, A.D. Johnson, D.K. Sanghera, O. Melander, C. Jern, D. Strbian, I. Fernandez-Cadenas, W.T. Longstreth, A. Rolfs, J. Hata, D. Woo, J. Rosand, G. Pare, J.C. Hopewell, D. Saleheen, K. Stefansson, B.B. Worrall, S.J. Kittner, S. Seshadri, M. Fornage, H.S. Markus, J.M.M. Howson, Y. Kamatani, S. Debette, M. Dichgans, Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat. Genet. 50, 524–537 (2018). https://doi.org/10.1038/s41588-018-0058-3

Article  CAS  PubMed  PubMed Central  Google Scholar 

B.L. Pierce, H. Ahsan, T.J. Vanderweele, Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J. Epidemiol. 40, 740–752 (2011). https://doi.org/10.1093/ije/dyq151

Article  PubMed  Google Scholar 

N. Papadimitriou, N. Dimou, K.K. Tsilidis, B. Banbury, R.M. Martin, S.J. Lewis, N. Kazmi, T.M. Robinson, D. Albanes, K. Aleksandrova, S.I. Berndt, D. Timothy Bishop, H. Brenner, D.D. Buchanan, B. Bueno-de-Mesquita, P.T. Campbell, S. Castellví-Bel, A.T. Chan, J. Chang-Claude, M. Ellingjord-Dale, J.C. Figueiredo, S.J. Gallinger, G.G. Giles, E. Giovannucci, S.B. Gruber, A. Gsur, J. Hampe, H. Hampel, S. Harlid, T.A. Harrison, M. Hoffmeister, J.L. Hopper, L. Hsu, J. María Huerta, J.R. Huyghe, M.A. Jenkins, T.O. Keku, T. Kühn, C. La Vecchia, L. Le Marchand, C.I. Li, L. Li, A. Lindblom, N.M. Lindor, B. Lynch, S.D. Markowitz, G. Masala, A.M. May, R. Milne, E. Monninkhof, L. Moreno, V. Moreno, P.A. Newcomb, K. Offit, V. Perduca, P.D.P. Pharoah, E.A. Platz, J.D. Potter, G. Rennert, E. Riboli, M.-J. Sánchez, S.L. Schmit, R.E. Schoen, G. Severi, S. Sieri, M.L. Slattery, M. Song, C.M. Tangen, S.N. Thibodeau, R.C. Travis, A. Trichopoulou, C.M. Ulrich, F.J.B. van Duijnhoven, B. Van Guelpen, P. Vodicka, E. White, A. Wolk, M.O. Woods, A.H. Wu, U. Peters, M.J. Gunter, N. Murphy, Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis. Nat Commun. 11, 597 (2020). https://doi.org/10.1038/s41467-020-14389-8

Article  CAS  PubMed  PubMed Central  Google Scholar 

J. Bowden, W. Spiller, F. Del Greco M, N. Sheehan, J. Thompson, C. Minelli, G. Davey Smith, Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression. Int. J. Epidemiol. 47, 1264–1278 (2018). https://doi.org/10.1093/ije/dyy101

Article  PubMed  PubMed Central  Google Scholar 

M. Verbanck, C.-Y. Chen, B. Neale, R. Do, Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat. Genet. 50, 693–698 (2018). https://doi.org/10.1038/s41588-018-0099-7

Article  CAS  PubMed  PubMed Central  Google Scholar 

Q. Zhao, Y. Chen, J. Wang, D.S. Small, Powerful three-sample genome-wide design and robust statistical inference in summary-data Mendelian randomization. Int. J. Epidemiol. 48, 1478–1492 (2019). https://doi.org/10.1093/ije/dyz142

Article  PubMed  Google Scholar 

S. Burgess, A. Butterworth, S.G. Thompson, Mendelian randomization analysis with multiple genetic variants using summarized data. Genet. Epidemiol. 37, 658–665 (2013). https://doi.org/10.1002/gepi.21758

Article  PubMed  PubMed Central  Google Scholar 

F.D. Greco M, C. Minelli, N.A. Sheehan, J.R. Thompson, Detecting pleiotropy in Mendelian randomization studies with summary data and a continuous outcome. Sta.t Med. 34, 2926–2940 (2015). https://doi.org/10.1002/sim.6522

Article  Google Scholar 

G. Hemani, K. Tilling, G. Davey Smith, Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 13, e1007081 (2017). https://doi.org/10.1371/journal.pgen.1007081

Article  CAS  PubMed  PubMed Central  Google Scholar 

F. Giacco, M. Brownlee, Oxidative stress and diabetic complications. Circ. Res. 107, 1058–1070 (2010). https://doi.org/10.1161/CIRCRESAHA.110.223545

Article 

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