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Katherine P. Liao, MD, MPH
Associate Physician, Brigham and Women's Hospital
Associate Professor of Medicine, Harvard Medical School

Brigham and Women's Hospital
Department of Medicine
Rheumatology, Immunology
75 Francis Street
Boston, MA 02115

Research Email:

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Research Narrative:

Dr. 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. Dr. 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. Dr. 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, Dr. 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, Dr. 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.

Harvard School of Public Health, 2010, MPH
SUNY Downstate Medical Center, 2004, MD
Williams College, 1999, BA

Publications (Pulled from Harvard Catalyst Profiles):

1. Yu Z, Kim SC, Vanni K, Huang J, Desai R, Murphy SN, Solomon DH, Liao KP. Correction to: Association between inflammation and systolic blood pressure in RA compared to patients without RA. Arthritis Res Ther. 2019 Jul 08; 21(1):170.

2. Wallace ZS, Fu X, Liao K, Kallenberg CGM, Langford CA, Merkel PA, Monach P, Seo P, Specks U, Spiera R, St Clair EW, Zhang Y, Choi H, Stone JH. Disease Activity, ANCA-Type, and Lipid Levels in ANCA-Associated Vasculitis. Arthritis Rheumatol. 2019 Jun 04.

3. Zhao SS, Ermann J, Xu C, Lyu H, Tedeschi SK, Liao KP, Yoshida K, Moots RJ, Goodson NJ, Solomon DH. Comparison of comorbidities and treatment between ankylosing spondylitis and non-radiographic axial spondyloarthritis in the United States. Rheumatology (Oxford). 2019 May 12.

4. Yang N, Huang J, Frits M, Iannaccone C, Weinblatt ME, Rifai N, Shadick N, Bradwin G, Liao KP. Interference of tumor necrosis factor inhibitor treatments on soluble tumor necrosis factor receptor 2 levels in rheumatoid arthritis. Pract Lab Med. 2019 Aug; 16:e00122.

5. Liao KP, Solomon DH. Lipids and Cardiovascular Risk Through the Lens of Rheumatoid Arthritis. Arthritis Rheumatol. 2019 Apr 15.

6. Gronsbell J, Minnier J, Yu S, Liao K, Cai T. Automated feature selection of predictors in electronic medical records data. Biometrics. 2019 03; 75(1):268-277.

7. Hong C, Liao KP, Cai T. Semi-supervised validation of multiple surrogate outcomes with application to electronic medical records phenotyping. Biometrics. 2019 03; 75(1):78-89.

8. Ning W, Chan S, Beam A, Yu M, Geva A, Liao K, Mullen M, Mandl KD, Kohane I, Cai T, Yu S. Feature extraction for phenotyping from semantic and knowledge resources. J Biomed Inform. 2019 Mar; 91:103122.

9. Hejblum BP, Weber GM, Liao KP, Palmer NP, Churchill S, Shadick NA, Szolovits P, Murphy SN, Kohane IS, Cai T. Probabilistic record linkage of de-identified research datasets with discrepancies using diagnosis codes. Sci Data. 2019 01 08; 6:180298.

10. Jorge A, Castro VM, Barnado A, Gainer V, Hong C, Cai T, Cai T, Carroll R, Denny JC, Crofford L, Costenbader KH, Liao KP, Karlson EW, Feldman CH. Identifying lupus patients in electronic health records: Development and validation of machine learning algorithms and application of rule-based algorithms. Semin Arthritis Rheum. 2019 Aug; 49(1):84-90.