Challenges and Opportunities with Causal Discovery Algorithms: Application to Alzheimer’s Pathophysiology
Authors: Shen Xinpeng , Ma Sisi , Vemuri Prashanthi , Simon Gyorgy ,   the Alzheimer’s Disease Neuroimaging Initiative, Weiner Michael W. , Aisen Paul , Petersen Ronald , Jack Clifford R. , Saykin Andrew J. , Jagust William , Trojanowki John Q. , Toga Arthur W. , Beckett Laurel , Green Robert C. , Morris John , Shaw Leslie M. , Khachaturian Zaven , Sorensen Greg , Carrillo Maria , Kuller Lew , Raichle Marc , Paul Steven , Davies Peter , Fillit Howard , Hefti Franz , Holtzman David , Mesulam M. Marcel , Potter William , Snyder Peter , Schwartz Adam , Montine Tom , Thomas Ronald G. , Donohue Michael , Walter Sarah , Gessert Devon , Sather Tamie , Jiminez Gus , Balasubramanian Archana B. , Mason Jennifer , Sim Iris , Harvey Danielle , Bernstein Matthew , Fox Nick , Thompson Paul , Schuff Norbert , DeCArli Charles , Borowski Bret , Gunter Jeff , Senjem Matt , Jones David , Kantarci Kejal , Ward Chad , Koeppe Robert A. , Foster Norm , Reiman Eric M. , Chen Kewei , Mathis Chet , Landau Susan , Cairns Nigel J. , Franklin Erin , Taylor-Reinwald Lisa , Lee Virginia , Korecka Magdalena , Figurski Michal , Crawford Karen , Neu Scott , Foroud Tatiana M. , Potkin Steven , Faber Kelley , Kim Sungeun , Nho Kwangsik , Thal Leon , Buckholtz Neil , Albert Marilyn , Frank Richard , Hsiao John , Kaye Jeffrey , Quinn Joseph , Silbert Lisa , Lind Betty , Carter Raina , Dolen Sara , Schneider Lon S. , Pawluczyk Sonia , Beccera Mauricio , Teodoro Liberty , Spann Bryan M. , Brewer James , Vanderswag Helen , Fleisher Adam , Heidebrink Judith L. , Lord Joanne L. , Mason Sara S. , Albers Colleen S. , Knopman David , Johnson Kris , Doody Rachelle S. , Villanueva-Meyer Javier , Pavlik Valory , Shibley Victoria , Chowdhury Munir , Rountree Susan , Dang Mimi , Stern Yaakov , Honig Lawrence S. , Bell Karen L. , Ances Beau , Carroll Maria , Creech Mary L. , Franklin Erin , Mintun Mark A. , Schneider Stacy , Oliver Angela , Marson Daniel , Geldmacher David , Love Marissa Natelson , Griffith Randall , Clark David , Brockington John , Roberson Erik , Grossman Hillel , Mitsis Effie , Shah Raj C. , deToledo-Morrell Leyla , Duara Ranjan , Greig-Custo Maria T. , Barker Warren , Onyike Chiadi , D’Agostino Daniel , Kielb Stephanie , Sadowski Martin , Sheikh Mohammed O. , Ulysse Anaztasia , Gaikwad Mrunalini , Doraiswamy P. Murali , Petrella Jeffrey R. , Borges-Neto Salvador , Wong Terence Z. , Coleman Edward , Arnold Steven E. , Karlawish Jason H. , Wolk David A. , Clark Christopher M. , Smith Charles D. , Jicha Greg , Hardy Peter , Sinha Partha , Oates Elizabeth , Conrad Gary , Lopez Oscar L. , Oakley Mary Ann , Simpson Donna M. , Porsteinsson Anton P. , Goldstein Bonnie S. , Martin Kim , Makino Kelly M. , Ismail M. Saleem , Brand Connie , Preda Adrian , Nguyen Dana , Womack Kyle , Mathews Dana , Quiceno Mary , Levey Allan I. , Lah James J. , Cellar Janet S. , Burns Jeffrey M. , Swerdlow Russell H. , Brooks William M. , Apostolova Liana , Tingus Kathleen , Woo Ellen , Silverman Daniel H. S. , Lu Po H. , Bartzokis George , Graff-Radford Neill R , Parfitt Francine , Poki-Walker Kim , Farlow Martin R. , Hake Ann Marie , Matthews Brandy R. , Brosch Jared R. , Herring Scott , van Dyck Christopher H. , Carson Richard E. , MacAvoy Martha G. , Varma Pradeep , Chertkow Howard , Bergman Howard , Hosein Chris , Black Sandra , Stefanovic Bojana , Caldwell Curtis , Hsiung Ging-Yuek Robin , Mudge Benita , Sossi Vesna , Feldman Howard , Assaly Michele , Finger Elizabeth , Pasternack Stephen , Rachisky Irina , Rogers John , Trost Dick , Kertesz Andrew , Bernick Charles , Munic Donna , Rogalski Emily , Lipowski Kristine , Weintraub Sandra , Bonakdarpour Borna , Kerwin Diana , Wu Chuang-Kuo , Johnson Nancy , Sadowsky Carl , Villena Teresa , Turner Raymond Scott , Johnson Kathleen , Reynolds Brigid , Sperling Reisa A. , Johnson Keith A. , Marshall Gad , Yesavage Jerome , Taylor Joy L. , Lane Barton , Rosen Allyson , Tinklenberg Jared , Sabbagh Marwan N. , Belden Christine M. , Jacobson Sandra A. , Sirrel Sherye A. , Kowall Neil , Killiany Ronald , Budson Andrew E. , Norbash Alexander , Johnson Patricia Lynn , Obisesan Thomas O. , Wolday Saba , Allard Joanne , Lerner Alan , Ogrocki Paula , Tatsuoka Curtis , Fatica Parianne , Fletcher Evan , Maillard Pauline , Olichney John , DeCarli Charles , Carmichael Owen , Kittur Smita , Borrie Michael , Lee T.-Y. , Bartha Rob , Johnson Sterling , Asthana Sanjay , Carlsson Cynthia M. , Tariot Pierre , Burke Anna , Milliken Ann Marie , Trncic Nadira , Fleisher Adam , Reeder Stephanie , Bates Vernice , Capote Horacio , Rainka Michelle , Scharre Douglas W. , Kataki Maria , Kelly Brendan , Zimmerman Earl A. , Celmins Dzintra , Brown Alice D. , Pearlson Godfrey D. , Blank Karen , Anderson Karen , Flashman Laura A. , Seltzer Marc , Hynes Mary L. , Santulli Robert B. , Sink Kaycee M. , Gordineer Leslie , Williamson Jeff D. , Garg Pradeep , Watkins Franklin , Ott Brian R. , Tremont Geoffrey , Daiello Lori A. , Salloway Stephen , Malloy Paul , Correia Stephen , Rosen Howard J. , Miller Bruce L. , Perry David , Mintzer Jacobo , Spicer Kenneth , Bachman David , Pomara Nunzio , Hernando Raymundo , Sarrael Antero , Schultz Susan K. , Smith Karen Ekstam , Koleva Hristina , Nam Ki Won , Shim Hyungsub , Relkin Norman , Chaing Gloria , Lin Michael , Ravdin Lisa , Smith Amanda , Raj Balebail Ashok , Fargher Kristin 
Published: February 2020

Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately discover known causal relationships. We used Alzheimer’s disease (AD), a complex progressive disease, as a model because the well-established evidence provides a “gold-standard” causal graph for evaluation. We evaluated two CSD methods, Fast Causal Inference (FCI) and Fast Greedy Equivalence Search (FGES) in their ability to discover this structure from data collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used structural equation models (which is not designed for CSD) as control. We applied these methods under three scenarios defined by increasing amounts of background knowledge provided to the methods. The methods were evaluated by comparing the resulting causal relationships with the “gold standard” graph that was constructed from literature. Dedicated CSD methods managed to discover graphs that nearly coincided with the gold standard. For best results, CSD algorithms should be used with longitudinal data providing as much prior knowledge as possible.