US 12,469,605 B2
Machine learning algorithm for predicting clinical outcomes and identifying drug targets in ischemic stroke
Keith R. Pennypacker, Lexington, KY (US); Justin F. Fraser, Lexington, KY (US); and Qiang Cheng, Lexington, KY (US)
Assigned to University of Kentucky Research Foundation, Lexington, KY (US)
Appl. No. 17/768,181
Filed by UNIVERSITY OF KENTUCKY RESEARCH FOUNDATION, Lexington, KY (US)
PCT Filed Oct. 13, 2020, PCT No. PCT/US2020/055407
§ 371(c)(1), (2) Date Apr. 11, 2022,
PCT Pub. No. WO2021/072404, PCT Pub. Date Apr. 15, 2021.
Claims priority of provisional application 62/945,705, filed on Dec. 9, 2019.
Claims priority of provisional application 62/913,474, filed on Oct. 10, 2019.
Prior Publication US 2023/0134886 A1, May 4, 2023
Int. Cl. C12Q 1/68 (2018.01); C12P 19/34 (2006.01); C12Q 1/6883 (2018.01); G16B 25/10 (2019.01); G16B 40/20 (2019.01); G16H 50/30 (2018.01)
CPC G16H 50/30 (2018.01) [C12Q 1/6883 (2013.01); G16B 25/10 (2019.02); G16B 40/20 (2019.02); C12Q 2600/158 (2013.01)] 5 Claims
 
1. A method for treating a stroke in a subject, the method comprising:
a) obtaining from the subject: a proximal sample comprising blood collected proximal to a cerebral thrombus; and a distal sample comprising blood collected distal to the cerebral thrombus;
b) detecting the expression level of IFNA2, CCR4, IL5, IL9, IL7 and CCR3 mRNAs in the proximal sample and the distal sample;
c) detecting an increased expression level of IFNA2, CCR4, IL5, IL9, IL7 and CCR3 CCR3 mRNAs in the proximal sample as compared to the distal sample;
d) predicting a larger edema or infarct volume in the subject as compared to a control subject in which the expression level of IFNA2, CCR4, IL5, IL9, IL7 and CCR3 mRNAs are not increased in a proximal sample as compared to a distal sample; and
e) treating the stroke in the subject, where the treatment comprises: mechanical thrombectomy (MT), administration of tissue plasminogen activator (tPA), or administration of an IL9 neutralizing antibody.