Person: Weinblatt, Michael
Loading...
Email Address
AA Acceptance Date
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Weinblatt
First Name
Michael
Name
Weinblatt, Michael
12 results
Search Results
Now showing 1 - 10 of 12
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 Development of a Health Care Utilisation Data-Based Index for Rheumatoid Arthritis Severity: A Preliminary Study(Springer Science and Business Media LLC, 2008-08-21) Ting, Gladys; Schneeweiss, Sebastian; Scranton, Richard E.; Katz, Jeffrey; Weinblatt, Michael; Young, Melissa; Avorn, Jerome; Solomon, DanielIntroduction Health care utilisation ('claims') databases contain information about millions of patients and are an important source of information for a variety of study types. However, they typically do not contain information about disease severity. The goal of the present study was to develop a health care claims index for rheumatoid arthritis (RA) severity using a previously developed medical records-based index for RA severity (RA medical records-based index of severity [RARBIS]). Methods The study population consisted of 120 patients from the Veteran's Administration (VA) Health System. We previously demonstrated the construct validity of the RARBIS and established its convergent validity with the Disease Activity Score (DAS28). Potential claims-based indicators were entered into a linear regression model as independent variables and the RARBIS as the dependent variable. The claims-based index for RA severity (CIRAS) was created using the coefficients from models with the highest coefficient of determination (R2) values selected by automated modelling procedures. To compare our claims-based index with our medical records-based index, we examined the correlation between the CIRAS and the RARBIS using Spearman non-parametric tests. Results The forward selection models yielded the highest model R2 for both the RARBIS with medications (R2 = 0.31) and the RARBIS without medications (R2 = 0.26). Components of the CIRAS included tests for inflammatory markers, number of chemistry panels and platelet counts ordered, rheumatoid factor, the number of rehabilitation and rheumatology visits, and Felty's syndrome diagnosis. The CIRAS demonstrated moderate correlations with the RARBIS with medication and the RARBIS without medication sub-scales. Conclusion We developed the CIRAS that showed moderate correlations with a previously validated records-based index of severity. The CIRAS may serve as a potentially important tool in adjusting for RA severity in pharmacoepidemiology studies of RA treatment and complications using health care utilisation data.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 Pathologically Expanded Peripheral T Helper Cell Subset Drives B Cells in Rheumatoid Arthritis(Springer Science and Business Media LLC, 2017-02-02) Rao, Deepak; Gurish, Michael F.; Marshall, Jennifer L.; Slowikowski, Kamil; Fonseka, Chamith Y.; Liu, Yanyan; Donlin, Laura T.; Henderson, Lauren; Wei, Kevin; Mizoguchi, Fumitaka; Teslovich, Nikola; Weinblatt, Michael; Massarotti, Elena; Coblyn, Jonathan; Helfgott, Simon; Lee, Yvonne C.; Todd, Derrick; Bykerk, Vivian P.; Goodman, Susan M.; Pernis, Alessandra B.; Ivashkiv, Lionel B.; Karlson, Elizabeth; Nigrovic, Peter; Filer, Andrew; Buckley, Christopher D.; Lederer, James; Raychaudhuri, Soumya; Brenner, MichaelCD4+ T cells are central mediators of autoimmune pathology; however, defining their key effector functions in specific autoimmune diseases remains challenging. Pathogenic CD4+ T cells within affected tissues may be identified by expression of markers of recent activation1. Here, we used mass cytometry to evaluate activated T cells in joint tissue from patients with rheumatoid arthritis (RA), a chronic immune-mediated arthritis that affects up to 1% of the population2. This approach revealed a strikingly expanded population of PD-1hi CXCR5- CD4+ T cells in RA synovium. These cells are not exhausted. Rather, multidimensional cytometry, transcriptomics, and functional assays define a population of PD-1hi CXCR5- ‘peripheral helper’ T (Tph) cells that express factors enabling B cell help, including IL-21, CXCL13, ICOS, and MAF. Like PD-1hi CXCR5+ T follicular helper (Tfh) cells, Tph cells induce plasma cell differentiation in vitro via IL-21 and SLAMF5-interactions3,4. However, global transcriptomics robustly separate Tph cells from Tfh cells, with altered expression of Bcl6 and Blimp-1 and unique expression of chemokine receptors that direct migration to inflamed sites, such as CCR2, CX3CR1, and CCR5, in Tph cells. Tph cells appear uniquely poised to promote B cell responses and antibody production within pathologically inflamed non-lymphoid tissues.Publication 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.