Katherine Phoenix Liao, M.D.
Katherine Phoenix Liao, M.D.
Assistant Professor of Medicine, BWH
Assistant Professor of Biomedical Informatics, HMS (Secondary)
Brigham and Women's Hospital Rheumatology - PBB-B3 75 Francis St Boston, MA 02115

Katherine Liao is a clinical investigator and practicing rheumatologist. The mission of her lab her lab is two-fold: (1) is to study rheumatoid arthritis (RA), and the clinical and genetic factors that lead to outcomes such as cardiovascular disease and severe joint damage, and (2) is to apply and develop bioinformatics methods to utilize big data for clinical and translational research studies. Liao’s research focuses on applying methods such as natural language processing to electronic medical record (EMR) data to perform clinical studies in RA and other conditions. Heart disease is the leading cause of death in patients with RA. This high risk has been attributed to inflammation, which is an important risk factor for heart disease in the general population. Determining these links can identify strategies to reduce CV risk in RA, as well as lead to potential targets of treatment in the general population. Liao is the PI of the R01 funded study, Lipids, Inflammation and CV risk in RA (LiiRA). The goal of LiiRA is to investigate how inflammation may modify important traditional cardiovascular risk factors such as cholesterol and blood pressure, and the impact of these modifications on CV risk. She is also a co-investigator on an NIH U01 multi-center RCT, Treatment Against RA and Effect on FDG PET CT (TARGET). TARGET specifically tests the hypothesis that reducing inflammation, reduces vascular inflammation and CV risk in RA. In line with her research interests, Liao is co-Director of the Cardiovascular Rheumatology Clinic at Brigham and Women’s Hospital. Through her work with the Informatics for Integrating Biology and the Bedside (i2b2) project, Liao led the team to develop an EMR research platform for RA studies. This platform integrated clinical and biomarker data (e.g. clinical EMR data, genetics, autoantibody data) allowing for both traditional genetic association studies as well as new approaches for data analyses such as the Phenome Wide Association Study (PheWAS). Using this platform, she collaborates closely with investigators from the fields of biostatistics and bioinformatics to apply novel methods to study focused clinical questions such as CVD in RA. Currently, she is leading a pilot project to port and further develop these methods at VA Boston Healthcare using nationwide VA data with a goal to establish an EMR research platform at the VA.

Impact of Changes in Inflammation on Estimated Ten-Year Cardiovascular Risk in Rheumatoid Arthritis.
Authors: Yu Z, Yang N, Everett BM, Frits M, Iannaccone C, Coblyn J, Weinblatt M, Shadick N, Solomon DH, Liao KP.
Arthritis Rheumatol
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Association Between Anti-Citrullinated Fibrinogen Antibodies and Coronary Artery Disease in Rheumatoid Arthritis.
Authors: Hejblum BP, Cui J, Lahey LJ, Cagan A, Sparks JA, Sokolove J, Cai T, Liao KP.
Arthritis Care Res (Hoboken)
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Pseudogout among Patients Fulfilling a Billing Code Algorithm for Calcium Pyrophosphate Deposition Disease.
Authors: Tedeschi SK, Solomon DH, Liao KP.
Rheumatol Int
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Association between inflammation and systolic blood pressure in RA compared to patients without RA.
Authors: Yu Z, Kim SC, Vanni K, Huang J, Desai R, Murphy SN, Solomon DH, Liao KP.
Arthritis Res Ther
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Cardiovascular Safety of Biologics and JAK Inhibitors in Patients with Rheumatoid Arthritis.
Authors: Kang EH, Liao KP, Kim SC.
Curr Rheumatol Rep
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Lipids in RA: Is Less Not Necessarily More?
Authors: Plutzky J, Liao KP.
Curr Rheumatol Rep
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Performance of the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis in a geographically distant National Register-based cohort: an external validation.
Authors: Ljung L, Ueda P, Liao KP, Greenberg JD, Etzel CJ, Solomon DH, Askling J.
RMD Open
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A phenotyping algorithm to identify acute ischemic stroke accurately from a national biobank: the Million Veteran Program.
Authors: Imran TF, Posner D, Honerlaw J, Vassy JL, Song RJ, Ho YL, Kittner SJ, Liao KP, Cai T, O'Donnell CJ, Djousse L, Gagnon DR, Gaziano JM, Wilson PW, Cho K.
Clin Epidemiol
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Enabling phenotypic big data with PheNorm.
Authors: Yu S, Ma Y, Gronsbell J, Cai T, Ananthakrishnan AN, Gainer VS, Churchill SE, Szolovits P, Murphy SN, Kohane IS, Liao KP, Cai T.
J Am Med Inform Assoc
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Transethnic meta-analysis identifies GSDMA and PRDM1 as susceptibility genes to systemic sclerosis.
Authors: Terao C, Kawaguchi T, Dieude P, Varga J, Kuwana M, Hudson M, Kawaguchi Y, Matucci-Cerinic M, Ohmura K, Riemekasten G, Kawasaki A, Airo P, Horita T, Oka A, Hachulla E, Yoshifuji H, Caramaschi P, Hunzelmann N, Baron M, Atsumi T, Hassoun P, Torii T, Takahashi M, Tabara Y, Shimizu M, Tochimoto A, Ayuzawa N, Yanagida H, Furukawa H, Tohma S, Hasegawa M, Fujimoto M, Ishikawa O, Yamamoto T, Goto D, Asano Y, Jinnin M, Endo H, Takahashi H, Takehara K, Sato S, Ihn H, Raychaudhuri S, Liao K, Gregersen P, Tsuchiya N, Riccieri V, Melchers I, Valentini G, Cauvet A, Martinez M, Mimori T, Matsuda F, Allanore Y.
Ann Rheum Dis
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