Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network

Hakan Ay, Ethem Murat Arsava, Gunnar Andsberg, Thomas Benner, Robert D. Brown, Sherita N. Chapman, John W. Cole, Hossein Delavaran, Martin Dichgans, Gunnar Engström, Eva Giralt-Steinhauer, Raji P. Grewal, Katrina Gwinn, Christina Jern, Jordi Jimenez-Conde, Katarina Jood, Michael Katsnelson, Brett Kissela, Steven J. Kittner, Dawn O. Kleindorfer & 34 others Daniel L. Labovitz, Silvia Lanfranconi, Jin Moo Lee, Manuel Lehm, Robin Lemmens, Chris Levi, Linxin Li, Arne Lindgren, Hugh S. Markus, Patrick F. McArdle, Olle Melander, Bo Norrving, Leema Reddy Peddareddygari, Annie Pedersén, Joanna Pera, Kristiina Rannikmäe, Kathryn M. Rexrode, David Rhodes, Stephen S. Rich, Jaume Roquer, Jonathan Rosand, Peter M. Rothwell, Tatjana Rundek, Ralph L. Sacco, Reinhold Schmidt, Markus Schürks, Stephan Seiler, Pankaj Sharma, Agnieszka Slowik, Cathie Sudlow, Vincent Thijs, Rebecca Woodfield, Bradford B. Worrall, James F. Meschia

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Background and Purpose - NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium.

Methods - Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases.

Results - The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (0.73; 95% confidence interval, 0.70-0.75).

Conclusions - This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.

Original languageEnglish (US)
Pages (from-to)3589-3596
Number of pages8
JournalStroke
Volume45
Issue number12
DOIs
StatePublished - Dec 11 2014

Fingerprint

National Institute of Neurological Disorders and Stroke
Stroke
Phenotype
Confidence Intervals
Geographic Locations

Keywords

  • Classification
  • Pathogenesis
  • Phenotype

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Clinical Neurology
  • Advanced and Specialized Nursing

Cite this

Ay, H., Arsava, E. M., Andsberg, G., Benner, T., Brown, R. D., Chapman, S. N., ... Meschia, J. F. (2014). Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network. Stroke, 45(12), 3589-3596. https://doi.org/10.1161/STROKEAHA.114.007362

Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network. / Ay, Hakan; Arsava, Ethem Murat; Andsberg, Gunnar; Benner, Thomas; Brown, Robert D.; Chapman, Sherita N.; Cole, John W.; Delavaran, Hossein; Dichgans, Martin; Engström, Gunnar; Giralt-Steinhauer, Eva; Grewal, Raji P.; Gwinn, Katrina; Jern, Christina; Jimenez-Conde, Jordi; Jood, Katarina; Katsnelson, Michael; Kissela, Brett; Kittner, Steven J.; Kleindorfer, Dawn O.; Labovitz, Daniel L.; Lanfranconi, Silvia; Lee, Jin Moo; Lehm, Manuel; Lemmens, Robin; Levi, Chris; Li, Linxin; Lindgren, Arne; Markus, Hugh S.; McArdle, Patrick F.; Melander, Olle; Norrving, Bo; Peddareddygari, Leema Reddy; Pedersén, Annie; Pera, Joanna; Rannikmäe, Kristiina; Rexrode, Kathryn M.; Rhodes, David; Rich, Stephen S.; Roquer, Jaume; Rosand, Jonathan; Rothwell, Peter M.; Rundek, Tatjana; Sacco, Ralph L.; Schmidt, Reinhold; Schürks, Markus; Seiler, Stephan; Sharma, Pankaj; Slowik, Agnieszka; Sudlow, Cathie; Thijs, Vincent; Woodfield, Rebecca; Worrall, Bradford B.; Meschia, James F.

In: Stroke, Vol. 45, No. 12, 11.12.2014, p. 3589-3596.

Research output: Contribution to journalArticle

Ay, H, Arsava, EM, Andsberg, G, Benner, T, Brown, RD, Chapman, SN, Cole, JW, Delavaran, H, Dichgans, M, Engström, G, Giralt-Steinhauer, E, Grewal, RP, Gwinn, K, Jern, C, Jimenez-Conde, J, Jood, K, Katsnelson, M, Kissela, B, Kittner, SJ, Kleindorfer, DO, Labovitz, DL, Lanfranconi, S, Lee, JM, Lehm, M, Lemmens, R, Levi, C, Li, L, Lindgren, A, Markus, HS, McArdle, PF, Melander, O, Norrving, B, Peddareddygari, LR, Pedersén, A, Pera, J, Rannikmäe, K, Rexrode, KM, Rhodes, D, Rich, SS, Roquer, J, Rosand, J, Rothwell, PM, Rundek, T, Sacco, RL, Schmidt, R, Schürks, M, Seiler, S, Sharma, P, Slowik, A, Sudlow, C, Thijs, V, Woodfield, R, Worrall, BB & Meschia, JF 2014, 'Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network', Stroke, vol. 45, no. 12, pp. 3589-3596. https://doi.org/10.1161/STROKEAHA.114.007362
Ay H, Arsava EM, Andsberg G, Benner T, Brown RD, Chapman SN et al. Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network. Stroke. 2014 Dec 11;45(12):3589-3596. https://doi.org/10.1161/STROKEAHA.114.007362
Ay, Hakan ; Arsava, Ethem Murat ; Andsberg, Gunnar ; Benner, Thomas ; Brown, Robert D. ; Chapman, Sherita N. ; Cole, John W. ; Delavaran, Hossein ; Dichgans, Martin ; Engström, Gunnar ; Giralt-Steinhauer, Eva ; Grewal, Raji P. ; Gwinn, Katrina ; Jern, Christina ; Jimenez-Conde, Jordi ; Jood, Katarina ; Katsnelson, Michael ; Kissela, Brett ; Kittner, Steven J. ; Kleindorfer, Dawn O. ; Labovitz, Daniel L. ; Lanfranconi, Silvia ; Lee, Jin Moo ; Lehm, Manuel ; Lemmens, Robin ; Levi, Chris ; Li, Linxin ; Lindgren, Arne ; Markus, Hugh S. ; McArdle, Patrick F. ; Melander, Olle ; Norrving, Bo ; Peddareddygari, Leema Reddy ; Pedersén, Annie ; Pera, Joanna ; Rannikmäe, Kristiina ; Rexrode, Kathryn M. ; Rhodes, David ; Rich, Stephen S. ; Roquer, Jaume ; Rosand, Jonathan ; Rothwell, Peter M. ; Rundek, Tatjana ; Sacco, Ralph L. ; Schmidt, Reinhold ; Schürks, Markus ; Seiler, Stephan ; Sharma, Pankaj ; Slowik, Agnieszka ; Sudlow, Cathie ; Thijs, Vincent ; Woodfield, Rebecca ; Worrall, Bradford B. ; Meschia, James F. / Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network. In: Stroke. 2014 ; Vol. 45, No. 12. pp. 3589-3596.
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title = "Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network",
abstract = "Background and Purpose - NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium.Methods - Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases.Results - The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40{\%} to 54{\%} of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (0.72; 95{\%} confidence interval, 0.69-0.75) and phenotypic classifications (0.73; 95{\%} confidence interval, 0.70-0.75).Conclusions - This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.",
keywords = "Classification, Pathogenesis, Phenotype",
author = "Hakan Ay and Arsava, {Ethem Murat} and Gunnar Andsberg and Thomas Benner and Brown, {Robert D.} and Chapman, {Sherita N.} and Cole, {John W.} and Hossein Delavaran and Martin Dichgans and Gunnar Engstr{\"o}m and Eva Giralt-Steinhauer and Grewal, {Raji P.} and Katrina Gwinn and Christina Jern and Jordi Jimenez-Conde and Katarina Jood and Michael Katsnelson and Brett Kissela and Kittner, {Steven J.} and Kleindorfer, {Dawn O.} and Labovitz, {Daniel L.} and Silvia Lanfranconi and Lee, {Jin Moo} and Manuel Lehm and Robin Lemmens and Chris Levi and Linxin Li and Arne Lindgren and Markus, {Hugh S.} and McArdle, {Patrick F.} and Olle Melander and Bo Norrving and Peddareddygari, {Leema Reddy} and Annie Peders{\'e}n and Joanna Pera and Kristiina Rannikm{\"a}e and Rexrode, {Kathryn M.} and David Rhodes and Rich, {Stephen S.} and Jaume Roquer and Jonathan Rosand and Rothwell, {Peter M.} and Tatjana Rundek and Sacco, {Ralph L.} and Reinhold Schmidt and Markus Sch{\"u}rks and Stephan Seiler and Pankaj Sharma and Agnieszka Slowik and Cathie Sudlow and Vincent Thijs and Rebecca Woodfield and Worrall, {Bradford B.} and Meschia, {James F.}",
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T1 - Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network

AU - Ay, Hakan

AU - Arsava, Ethem Murat

AU - Andsberg, Gunnar

AU - Benner, Thomas

AU - Brown, Robert D.

AU - Chapman, Sherita N.

AU - Cole, John W.

AU - Delavaran, Hossein

AU - Dichgans, Martin

AU - Engström, Gunnar

AU - Giralt-Steinhauer, Eva

AU - Grewal, Raji P.

AU - Gwinn, Katrina

AU - Jern, Christina

AU - Jimenez-Conde, Jordi

AU - Jood, Katarina

AU - Katsnelson, Michael

AU - Kissela, Brett

AU - Kittner, Steven J.

AU - Kleindorfer, Dawn O.

AU - Labovitz, Daniel L.

AU - Lanfranconi, Silvia

AU - Lee, Jin Moo

AU - Lehm, Manuel

AU - Lemmens, Robin

AU - Levi, Chris

AU - Li, Linxin

AU - Lindgren, Arne

AU - Markus, Hugh S.

AU - McArdle, Patrick F.

AU - Melander, Olle

AU - Norrving, Bo

AU - Peddareddygari, Leema Reddy

AU - Pedersén, Annie

AU - Pera, Joanna

AU - Rannikmäe, Kristiina

AU - Rexrode, Kathryn M.

AU - Rhodes, David

AU - Rich, Stephen S.

AU - Roquer, Jaume

AU - Rosand, Jonathan

AU - Rothwell, Peter M.

AU - Rundek, Tatjana

AU - Sacco, Ralph L.

AU - Schmidt, Reinhold

AU - Schürks, Markus

AU - Seiler, Stephan

AU - Sharma, Pankaj

AU - Slowik, Agnieszka

AU - Sudlow, Cathie

AU - Thijs, Vincent

AU - Woodfield, Rebecca

AU - Worrall, Bradford B.

AU - Meschia, James F.

PY - 2014/12/11

Y1 - 2014/12/11

N2 - Background and Purpose - NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium.Methods - Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases.Results - The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (0.73; 95% confidence interval, 0.70-0.75).Conclusions - This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.

AB - Background and Purpose - NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium.Methods - Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases.Results - The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (0.73; 95% confidence interval, 0.70-0.75).Conclusions - This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.

KW - Classification

KW - Pathogenesis

KW - Phenotype

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