Person: Shadick, Nancy
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Shadick
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Nancy
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Shadick, Nancy
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Publication PTPN22.6, a Dominant Negative Isoform of PTPN22 and Potential Biomarker of Rheumatoid Arthritis(Public Library of Science, 2012) Chang, Hui-Hsin; Tai, Tzong-Shyuan; Lu, Bing; Iannaccone, Christine; Cernadas, Manuela; Weinblatt, Michael; Shadick, Nancy; Miaw, Shi-Chuen; Ho, I-ChengPTPN22 is a tyrosine phosphatase and functions as a damper of TCR signals. A C-to-T single nucleotide polymorphism (SNP) located at position 1858 of human PTPN22 cDNA and converting an arginine (R620) to tryptophan (W620) confers the highest risk of rheumatoid arthritis among non-HLA genetic variations that are known to be associated with this disease. The effect of the R-to-W conversion on the phosphatase activity of PTPN22 protein and the impact of the minor T allele of the C1858T SNP on the activation of T cells has remained controversial. In addition, how the overall activity of PTPN22 is regulated and how the R-to-W conversion contributes to rheumatoid arthritis is still poorly understood. Here we report the identification of an alternative splice form of human PTPN22, namely PTPN22.6. It lacks the nearly entire phosphatase domain and can function as a dominant negative isoform of the full length PTPN22. Although conversion of R620 to W620 in the context of PTPN22.1 attenuated T cell activation, expression of the tryptophan variant of PTPN22.6 reciprocally led to hyperactivation of human T cells. More importantly, the level of PTPN22.6 in peripheral blood correlates with disease activity of rheumatoid arthritis. Our data depict a model that can reconcile the conflicting observations on the functional impact of the C1858T SNP and also suggest that PTPN22.6 is a novel biomarker of rheumatoid arthritis.Publication Automatic Prediction of Rheumatoid Arthritis Disease Activity from the Electronic Medical Records(Public Library of Science, 2013) Lin, Chen; Karlson, Elizabeth; Canhao, Helena; Miller, Timothy; Dligach, Dmitriy; Chen, Pei Jun; Perez, Raul Natanael Guzman; Shen, Yuanyan; Weinblatt, Michael; Shadick, Nancy; Plenge, Robert M.; Savova, GuerganaObjective: We aimed to mine the data in the Electronic Medical Record to automatically discover patients' Rheumatoid Arthritis disease activity at discrete rheumatology clinic visits. We cast the problem as a document classification task where the feature space includes concepts from the clinical narrative and lab values as stored in the Electronic Medical Record. Materials and Methods The Training Set consisted of 2792 clinical notes and associated lab values. Test Set 1 included 1749 clinical notes and associated lab values. Test Set 2 included 344 clinical notes for which there were no associated lab values. The Apache clinical Text Analysis and Knowledge Extraction System was used to analyze the text and transform it into informative features to be combined with relevant lab values. Results: Experiments over a range of machine learning algorithms and features were conducted. The best performing combination was linear kernel Support Vector Machines with Unified Medical Language System Concept Unique Identifier features with feature selection and lab values. The Area Under the Receiver Operating Characteristic Curve (AUC) is 0.831 (σ = 0.0317), statistically significant as compared to two baselines (AUC = 0.758, σ = 0.0291). Algorithms demonstrated superior performance on cases clinically defined as extreme categories of disease activity (Remission and High) compared to those defined as intermediate categories (Moderate and Low) and included laboratory data on inflammatory markers. Conclusion: Automatic Rheumatoid Arthritis disease activity discovery from Electronic Medical Record data is a learnable task approximating human performance. As a result, this approach might have several research applications, such as the identification of patients for genome-wide pharmacogenetic studies that require large sample sizes with precise definitions of disease activity and response to therapies.Publication The Influence of Polygenic Risk Scores on Heritability of Anti-CCP Level in RA(2014) Cui, Jing; Taylor, Kimberly E.; Lee, Yvonne Claire; Källberg, Henrik; Weinblatt, Michael; Coblyn, Jonathan; Klareskog, Lars; Criswell, Lindsey A.; Gregersen, Peter K.; Shadick, Nancy; Plenge, Robert M.; Karlson, ElizabethObjective: To study genetic factors that influence quantitative anti-cyclic citrullinated peptide (anti-CCP) antibody levels in RA patients. Methods: We carried out a genome wide association study (GWAS) meta-analysis using 1,975 anti-CCP+ RA patients from 3 large cohorts, the Brigham Rheumatoid Arthritis Sequential Study (BRASS), North American Rheumatoid Arthritis Consortium (NARAC), and the Epidemiological Investigation of RA (EIRA). We also carried out a genome-wide complex trait analysis (GCTA) to estimate the heritability of anti-CCP levels. Results: GWAS-meta analysis showed that anti-CCP levels were most strongly associated with the human leukocyte antigen (HLA) region with a p-value of 2×10−11 for rs1980493. There were 112 SNPs in this region that exceeded the genome-wide significance threshold of 5×10−8, and all were in linkage disequilibrium (LD) with the HLA- DRB1*03 allele with LD r2 in the range of 0.25-0.88. Suggestive novel associations outside of the HLA region were also observed for rs8063248 (near the GP2 gene) with a p-value of 3×10−7. None of the known RA risk alleles (~52 loci) were associated with anti-CCP level. Heritability analysis estimated that 44% of anti-CCP variation was attributable to genetic factors captured by GWAS variants. Conclusions: Anti-CCP level is a heritable trait. HLA-DR3 and GP2 are associated with lower anti-CCP levels.Publication The Validity of a Rheumatoid Arthritis Medical Records-Based Index of Severity Compared with the DAS28(Springer Science and Business Media LLC, 2006) Sato, Masayo; Schneeweiss, Sebastian; Scranton, Richard; Katz, Jeffrey; Weinblatt, Michael; Avorn, Jerome; Ting, Gladys; Shadick, Nancy; Solomon, DanielThe objective of this work was to assess the convergent validity of a previously developed rheumatoid arthritis medical records-based index of severity (RARBIS) by comparing it with the 28-joint Disease Activity Score (DAS28). This study was conducted in subjects within the Brigham and Women's Hospital Rheumatoid Arthritis Sequential Study (BRASS). We selected 100 patients with rheumatoid arthritis (RA) from the BRASS with DAS28 scores equally distributed in four quartiles. The medical records were reviewed to calculate the RARBIS, which includes indicators from the following categories: prior surgical history, radiologic and laboratory findings, clinical and functional status, and extra-articular manifestations. The Spearman correlation between the RARBIS and the DAS28 was assessed in the total study population and in relevant subgroups. We re-weighted on subscales and recalculated the RARBIS score. This was performed based on findings of correlations between the DAS28 and subscales; and also the result from a multiple linear regression with the DAS28 (as a dependent variable) and five subscales (as independent variables). The mean RARBIS was 4.36 (range 0–11). Among the total study cohort, the RARBIS was moderately correlated with the DAS28 (r = 0.41, 95% confidence interval [CI] 0.23–0.56). In subgroup analyses, including age, gender, rheumatoid factor status, and disease duration, we found no statistically significant differences in the correlations. After re-weighting, the correlation between the RARBIS and the DAS28 was somewhat improved (r = 0.48, 95% CI 0.31–0.62). In conclusion, the RARBIS correlated moderately well with the DAS28 in this population. The RARBIS has both face and convergent validity for patients with RA and relevant subgroups and may have application for medical records studies in patients with RA.Publication A School-Based Intervention to Increase Lyme Disease Preventive Measures Among Elementary School-Aged Children(Mary Ann Liebert, Inc., 2016) Shadick, Nancy; Zibit, Melanie J.; Nardone, Elizabeth; DeMaria, Alfred; Iannaccone, Christine K.; Cui, JingAbstract Purpose: Educational interventions to reduce Lyme disease (LD) among at-risk school children have had little study. The purpose of this study was to evaluate whether a short in-class LD education program based on social learning theory and the Health Belief Model (HBM) impacted a child's knowledge, attitude, and preventive behavior. Methods: Students in grades 2–5 in 19 elementary schools were selected in an area that was highly endemic for LD. The children received an educational intervention or were on a wait list as controls. Their knowledge, attitudes, and self-reported preventive behaviors were surveyed before implementing the program and 1 year later. General linear regression analyses adjusting for age, gender, and baseline variables were used to measure the impact of the intervention. Results: There were 3570 participants in the study: 1562 received the intervention, and 2008 were controls. The mean age for both groups was 9.1 years, with 53% women in the intervention group and 50% women in the control group. The children in the intervention group increased their overall knowledge of LD more than the children in the control group (overall knowledge score improvement, mean difference (SD) 1.38 (1.3) vs. 0.36 (1.3) p < 0.0001). All children in classes receiving the intervention reported an increase in precautionary behavior, positive attitude toward taking precautions, and self-efficacy compared with the wait list controls. Two LD cases were confirmed during the follow-up period, one in the intervention group and one in the controls. Conclusions: These findings demonstrate that a short in-class educational program that includes elements of the HBM, including: (1) awareness and knowledge about the disease, (2) benefits of preventive behavior, and (3) confidence in ability to perform preventive behaviors can improve knowledge, attitude, and self-reported precautionary behavior among at-risk children. www.clinicaltrials.gov: NCT00594997Publication Validity of the Nurses’ health study physical activity questionnaire in estimating physical activity in adults with rheumatoid arthritis(BioMed Central, 2017) Quinn, Thomas; BS, Michelle Frits; von Heideken, Johan; Iannaccone, Christine; Shadick, Nancy; Weinblatt, Michael; Iversen, MauraBackground: Patients with rheumatoid arthritis (RA) demonstrate reduced aerobic capacity, excess cardiovascular risk, mobility limitations and are less physically active than their healthy peers. Physical activity may decrease RA disease activity through its anti-inflammatory effects and psychological and health benefits. To successfully manage RA symptoms and reduce cardiovascular risks associated with RA through increased physical activity (PA), accurate physical activity assessments are critical. Accelerometry is an objective physical activity measure, but not widely used. Validity of the Nurses’ Health Study physical activity questionnaire II (NHSPAQ) has not been determined for estimation of physical activity in RA. This study examined NHSPAQ validity in adults with RA compared to accelerometry-based metabolic equivalents determined (METs) and results of performance tests. We hypothesized NHSPAQ scores would correlate moderately (0.4–0.5) with accelerometer physical activity estimates. Methods: Thirty-five adults with RA (mean age [SD] 62 (Williams et. al, Health Qual Life Outcomes 10:28, 2012) years, 28 females (80%) recruited from a hospital-based clinic registry participated in a one-week accelerometry trial. Medical data was compiled. Participants completed the NHSPAQ, a self-paced 20-m walk test, and modified timed step test. Participants wore an accelerometer for 7 consecutive days, then completed a physical activity log and another NHSPAQ. Metabolic equivalents (METs) were derived from NHSPAQ and accelerometers using standardized formulas. NHSPAQ METs were correlated with accelerometer METs and data from performance measures. Results: Average disease duration was 21 years (SD = 11), 63% patients took biologics. The average weekly METs reported were 29 (SD = 33) and accelerometer METs were 33 (SD = 22). NHSPAQ METs correlated moderately with accelerometer-derived METs (r = 0.48 95% CI (0.15–0.70). Self-reported PA correlated moderately with Step Test performance (r = 0.50 95% CI (0.18–0.72). Conclusion: Patients with RA exhibit low physical activity levels. General fitness measures were moderately correlated with physical activity levels. A moderate significant correlation existed between NHSPAQ and accelerometry METs. These preliminary data suggest the NHSPAQ may be useful to describe physical activity levels in this population.Publication An external validation study reporting poor correlation between the claims-based index for rheumatoid arthritis severity and the disease activity score(BioMed Central, 2015) Desai, Rishi; Solomon, Daniel; Weinblatt, Michael; Shadick, Nancy; Kim, SeoyoungIntroduction: We conducted an external validation study to examine the correlation of a previously published claims-based index for rheumatoid arthritis severity (CIRAS) with disease activity score in 28 joints calculated by using C-reactive protein (DAS28-CRP) and the multi-dimensional health assessment questionnaire (MD-HAQ) physical function score. Methods: Patients enrolled in the Brigham and Women’s Hospital Rheumatoid Arthritis Sequential Study (BRASS) and Medicare were identified and their data from these two sources were linked. For each patient, DAS28-CRP measurement and MD-HAQ physical function scores were extracted from BRASS, and CIRAS was calculated from Medicare claims for the period of 365 days prior to the DAS28-CRP measurement. Pearson correlation coefficient between CIRAS and DAS28-CRP as well as MD-HAQ physical function scores were calculated. Furthermore, we considered several additional pharmacy and medical claims-derived variables as predictors for DAS28-CRP in a multivariable linear regression model in order to assess improvement in the performance of the original CIRAS algorithm. Results: In total, 315 patients with enrollment in both BRASS and Medicare were included in this study. The majority (81%) of the cohort was female, and the mean age was 70 years. The correlation between CIRAS and DAS28-CRP was low (Pearson correlation coefficient = 0.07, P = 0.24). The correlation between the calculated CIRAS and MD-HAQ physical function scores was also found to be low (Pearson correlation coefficient = 0.08, P = 0.17). The linear regression model containing additional claims-derived variables yielded model R2 of 0.23, suggesting limited ability of this model to explain variation in DAS28-CRP. Conclusions: In a cohort of Medicare-enrolled patients with established RA, CIRAS showed low correlation with DAS28-CRP as well as MD-HAQ physical function scores. Claims-based algorithms for disease activity should be rigorously tested in distinct populations in order to establish their generalizability before widespread adoption.Publication Effects of Achieving Target Measures in Rheumatoid Arthritis on Functional Status, Quality of Life, and Resource Utilization: Analysis of Clinical Practice Data(John Wiley and Sons Inc., 2016) Alemao, Evo; Joo, Seongjung; Kawabata, Hugh; Al, Maiwenn J.; Allison, Paul D.; Rutten‐van Mölken, Maureen P. M. H.; Frits, Michelle L.; Iannaccone, Christine K.; Shadick, Nancy; Weinblatt, MichaelObjective: To evaluate associations between achieving guideline‐recommended targets of disease activity, defined by the Disease Activity Score in 28 joints using C‐reactive protein level (DAS28‐CRP) <2.6, the Simplified Disease Activity Index (SDAI) ≤3.3, or the Clinical Disease Activity Index (CDAI) ≤2.8, and other health outcomes in a longitudinal observational study. Methods: Other defined thresholds included low disease activity (LDA), moderate (MDA), or severe disease activity (SDA). To control for intraclass correlation and estimate effects of independent variables on outcomes of the modified Health Assessment Questionnaire (M‐HAQ), the EuroQol 5‐domain (EQ‐5D; a quality‐of‐life measure), hospitalization, and durable medical equipment (DME) use, we employed mixed models for continuous outcomes and generalized estimating equations for binary outcomes. Results: Among 1,297 subjects, achievement (versus nonachievement) of recommended disease targets was associated with enhanced physical functioning and lower health resource utilization. After controlling for baseline covariates, achievement of disease targets (versus LDA) was associated with significantly enhanced physical functioning based on SDAI ≤3.3 (ΔM‐HAQ −0.047; P = 0.0100) and CDAI ≤2.8 (−0.073; P = 0.0003) but not DAS28‐CRP <2.6 (−0.022; P = 0.1735). Target attainment was associated with significantly improved EQ‐5D (0.022–0.096; P < 0.0030 versus LDA, MDA, or SDA). Patients achieving guideline‐recommended disease targets were 36–45% less likely to be hospitalized (P < 0.0500) and 23–45% less likely to utilize DME (P < 0.0100). Conclusion: Attaining recommended target disease‐activity measures was associated with enhanced physical functioning and health‐related quality of life. Some health outcomes were similar in subjects attaining guideline targets versus LDA. Achieving LDA is a worthy clinical objective in some patients.Publication Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis(Nature Publishing Group, 2016) Sieberts, Solveig K.; Zhu, Fan; García-García, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornés, Oriol; Guney, Emre; Li, Hongdong; Marín, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O.; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S. K.; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-ud-din, Muhammad; Azencott, Chloe-Agathe; Bellón, Víctor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R.; Marttinen, Pekka; Mezlini, Aziz M.; Molparia, Bhuvan; Pirinen, Matti; Saarela, Janna; Samwald, Matthias; Stoven, Véronique; Tang, Hao; Tang, Jing; Torkamani, Ali; Vert, Jean-Phillipe; Wang, Bo; Wang, Tao; Wennerberg, Krister; Wineinger, Nathan E.; Xiao, Guanghua; Xie, Yang; Yeung, Rae; Zhan, Xiaowei; Zhao, Cheng; Calaza, Manuel; Elmarakeby, Haitham; Heath, Lenwood S.; Long, Quan; Moore, Jonathan D.; Opiyo, Stephen Obol; Savage, Richard S.; Zhu, Jun; Greenberg, Jeff; Kremer, Joel; Michaud, Kaleb; Barton, Anne; Coenen, Marieke; Mariette, Xavier; Miceli, Corinne; Shadick, Nancy; Weinblatt, Michael; de Vries, Niek; Tak, Paul P.; Gerlag, Danielle; Huizinga, Tom W. J.; Kurreeman, Fina; Allaart, Cornelia F.; Louis Bridges Jr., S.; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K.; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M.Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Publication Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis(Public Library of Science, 2013) Cui, Jing; Stahl, Eli A.; Saevarsdottir, Saedis; Miceli, Corinne; Diogo, Dorothee; Trynka, Gosia; Raj, Towfique; Mirkov, Maša Umiċeviċ; Canhao, Helena; Ikari, Katsunori; Terao, Chikashi; Okada, Yukinori; Wedrén, Sara; Askling, Johan; Yamanaka, Hisashi; Momohara, Shigeki; Taniguchi, Atsuo; Ohmura, Koichiro; Matsuda, Fumihiko; Mimori, Tsuneyo; Gupta, Namrata; Kuchroo, Manik; Morgan, Ann W.; Isaacs, John D.; Wilson, Anthony G.; Hyrich, Kimme L.; Herenius, Marieke; Doorenspleet, Marieke E.; Tak, Paul-Peter; Crusius, J. Bart A.; van der Horst-Bruinsma, Irene E.; Wolbink, Gert Jan; van Riel, Piet L. C. M.; van de Laar, Mart; Guchelaar, Henk-Jan; Shadick, Nancy; Allaart, Cornelia F.; Huizinga, Tom W. J.; Toes, Rene E. M.; Kimberly, Robert P.; Bridges, S. Louis; Criswell, Lindsey A.; Moreland, Larry W.; Fonseca, João Eurico; de Vries, Niek; Stranger, Barbara E.; De Jager, Philip; Raychaudhuri, Soumya; Weinblatt, Michael; Gregersen, Peter K.; Mariette, Xavier; Barton, Anne; Padyukov, Leonid; Coenen, Marieke J. H.; Karlson, Elizabeth; Plenge, Robert M.Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10−8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10−11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry.