Katherine Phoenix Liao, MD, MPH

Katherine Liao, MD, MPH

Associate Professor of Medicine, Brigham and Women's Hospital
Associate Professor of Biomedical Informatics, Harvard Medical School (Secondary)

Brigham and Women's Hospital Rheumatology - PBB-B3 75 Francis St Boston, MA

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.

Modeling disease severity in multiple sclerosis using electronic health records.
Authors: Xia Z, Secor E, Chibnik LB, Bove RM, Cheng S, Chitnis T, Cagan A, Gainer VS, Chen PJ, Liao KP, Shaw SY, Ananthakrishnan AN, Szolovits P, Weiner HL, Karlson EW, Murphy SN, Savova GK, Cai T, Churchill SE, Plenge RM, Kohane IS, De Jager PL.
PLoS One
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Portability of an algorithm to identify rheumatoid arthritis in electronic health records.
Authors: Carroll RJ, Thompson WK, Eyler AE, Mandelin AM, Cai T, Zink RM, Pacheco JA, Boomershine CS, Lasko TA, Xu H, Karlson EW, Perez RG, Gainer VS, Murphy SN, Ruderman EM, Pope RM, Plenge RM, Kho AN, Liao KP, Denny JC.
J Am Med Inform Assoc
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Use of a multiethnic approach to identify rheumatoid- arthritis-susceptibility loci, 1p36 and 17q12.
Authors: Kurreeman FA, Stahl EA, Okada Y, Liao K, Diogo D, Raychaudhuri S, Freudenberg J, Kochi Y, Patsopoulos NA, Gupta N, Sandor C, Bang SY, Lee HS, Padyukov L, Suzuki A, Siminovitch K, Worthington J, Gregersen PK, Hughes LB, Reynolds RJ, Bridges SL, Bae SC, Yamamoto K, Plenge RM.
Am J Hum Genet
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Clinical predictors of erosion-free status in rheumatoid arthritis: a prospective cohort study.
Authors: Liao KP, Weinblatt ME, Cui J, Iannaccone C, Chibnik LB, Lu B, Coblyn JS, Shadick NA, Solomon DH.
Rheumatology (Oxford)
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All that glitters is not gold--standardizing diagnosis in rheumatoid arthritis studies.
Authors: Liao KP, Bykerk V.
J Rheumatol
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The end of rheumatoid factor as we know it?
Authors: Liao KP, Weinblatt ME, Solomon DH.
Arthritis Rheum
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Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records.
Authors: Kurreeman F, Liao K, Chibnik L, Hickey B, Stahl E, Gainer V, Li G, Bry L, Mahan S, Ardlie K, Thomson B, Szolovits P, Churchill S, Murphy SN, Cai T, Raychaudhuri S, Kohane I, Karlson E, Plenge RM.
Am J Hum Genet
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Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset.
Authors: Chibnik LB, Keenan BT, Cui J, Liao KP, Costenbader KH, Plenge RM, Karlson EW.
PLoS One
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The 2010 American College of Rheumatology/European League Against Rheumatism classification criteria for rheumatoid arthritis: Phase 2 methodological report.
Authors: Neogi T, Aletaha D, Silman AJ, Naden RL, Felson DT, Aggarwal R, Bingham CO, Birnbaum NS, Burmester GR, Bykerk VP, Cohen MD, Combe B, Costenbader KH, Dougados M, Emery P, Ferraccioli G, Hazes JM, Hobbs K, Huizinga TW, Kavanaugh A, Kay J, Khanna D, Kvien TK, Laing T, Liao K, Mease P, Ménard HA, Moreland LW, Nair R, Pincus T, Ringold S, Smolen JS, Stanislawska-Biernat E, Symmons D, Tak PP, Upchurch KS, Vencovský J, Wolfe F, Hawker G.
Arthritis Rheum
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Electronic medical records for discovery research in rheumatoid arthritis.
Authors: Liao KP, Cai T, Gainer V, Goryachev S, Zeng-treitler Q, Raychaudhuri S, Szolovits P, Churchill S, Murphy S, Kohane I, Karlson EW, Plenge RM.
Arthritis Care Res (Hoboken)
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