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. KleindorferDaniel 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 journalArticlepeer-review

40 Scopus citations


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
Issue number12
StatePublished - Dec 11 2014


  • Classification
  • Pathogenesis
  • Phenotype

ASJC Scopus subject areas

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


Dive into the research topics of 'Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network'. Together they form a unique fingerprint.

Cite this