:

Eloi Gagnon1, Iyas Daghlas1, Loukas Zagkos1

  • 1From the Quebec Heart and Lung Institute (E.G., B.J.A.), Laval University, Quebec, Canada; Department of Neurology (I.D.), University of California San Francisco; Department of Epidemiology and Biostatistics (L.Z., D.G.), School of Public Health, Imperial College London, United Kingdom; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (M.S.), University of Texas Health Sciences Center, San Antonio; Broad Institute of MIT and Harvard (M.K.G., C.D.A.), Cambridge, MA; Institute for Stroke and Dementia Research (ISD) (M.K.G.), University Hospital, LMU Munich, Germany; Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital; Department of Neurology (C.D.A.), Brigham and Women's Hospital, Boston, MA; Department of Public Health (H.T.C.), Section of Epidemiology, University of Copenhagen, Denmark; MRC Biostatistics Unit (S.B.), and Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Medicine (B.J.A.), Faculty of Medicine, Université Laval, Québec, Canada.

Neurology
|January 23, 2024
PubMed
概括

门德尔随机化 (MR) 在神经学中使用遗传数据进行因果推断. 这种强有力的方法有助于理解神经系统疾病,药物发现,并提供了对病理生理学的见解.