Katherine P. Liao

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

National Lipid Association Recommendations for Patient-Centered Management of Dyslipidemia: Part 2

An Expert Panel convened by the National Lipid Association previously developed a consensus set of recommendations for the patient-centered management of dyslipidemia in clinical medicine (part 1). These were guided by the principle that reducing elevated levels of atherogenic cholesterol (non-high-density lipoprotein cholesterol and low-density lipoprotein cholesterol) reduces the risk for atherosclerotic cardiovascular disease. This document represents a continuation of the National Lipid Association recommendations developed by a diverse panel of experts who examined the evidence base and provided recommendations regarding the following topics: (1) lifestyle therapies; (2) groups with special considerations, including children and adolescents, women, older patients, certain ethnic and racial groups, patients infected with human immunodeficiency virus, patients with rheumatoid arthritis, and patients with residual risk despite statin and lifestyle therapies; and (3) strategies to improve patient outcomes by increasing adherence and using team-based collaborative care.

Electronic medical records for discovery research in rheumatoid arthritis

Electronic medical records (EMRs) are a rich data source for discovery research but are underutilized due to the difficulty of extracting highly accurate clinical data. We assessed whether a classification algorithm incorporating narrative EMR data (typed physician notes) more accurately classifies subjects with rheumatoid arthritis (RA) compared with an algorithm using codified EMR data alone.

Normalization of plasma 25-hydroxy vitamin D is associated with reduced risk of surgery in Crohn's disease.

Background:Vitamin D may have an immunologic role in Crohn’s disease (CD) and ulcerative colitis (UC). Retrospective studies suggested a weak association between vitamin D status and disease activity but have significant limitations. Methods:Using a multi-institution inflammatory bowel disease cohort, we identified all patients with CD and UC who had at least one measured plasma 25-hydroxy vitamin D (25(OH)D). Plasma 25(OH)D was considered sufficient at levels ≥30 ng/mL. Logistic regression models adjusting for potential confounders were used to identify impact of measured plasma 25(OH)D on subsequent risk of inflammatory bowel disease–related surgery or hospitalization. In a subset of patients where multiple measures of 25(OH)D were available, we examined impact of normalization of vitamin D status on study outcomes. Results:Our study included 3217 patients (55% CD; mean age, 49 yr). The median lowest plasma 25(OH)D was 26 ng/mL (interquartile range, 17–35 ng/mL). In CD, on multivariable analysis, plasma 25(OH)D <20 ng/mL was associated with an increased risk of surgery (odds ratio, 1.76; 95% confidence interval, 1.24–2.51) and inflammatory bowel disease–related hospitalization (odds ratio, 2.07; 95% confidence interval, 1.59–2.68) compared with those with 25(OH)D ≥30 ng/mL. Similar estimates were also seen for UC. Furthermore, patients with CD who had initial levels <30 ng/mL but subsequently normalized their 25(OH)D had a reduced likelihood of surgery (odds ratio, 0.56; 95% confidence interval, 0.32–0.98) compared with those who remained deficient. Conclusion:Low plasma 25(OH)D is associated with increased risk of surgery and hospitalizations in both CD and UC, and normalization of 25(OH)D status is associated with a reduction in the risk of CD-related surgery.

Portability of an algorithm to identify rheumatoid arthritis in electronic health records.

OBJECTIVES Electronic health records (EHR) can allow for the generation of large cohorts of individuals with given diseases for clinical and genomic research. A rate-limiting step is the development of electronic phenotype selection algorithms to find such cohorts. This study evaluated the portability of a published phenotype algorithm to identify rheumatoid arthritis (RA) patients from EHR records at three institutions with different EHR systems. MATERIALS AND METHODS Physicians reviewed charts from three institutions to identify patients with RA. Each institution compiled attributes from various sources in the EHR, including codified data and clinical narratives, which were searched using one of two natural language processing (NLP) systems. The performance of the published model was compared with locally retrained models. RESULTS Applying the previously published model from Partners Healthcare to datasets from Northwestern and Vanderbilt Universities, the area under the receiver operating characteristic curve was found to be 92% for Northwestern and 95% for Vanderbilt, compared with 97% at Partners. Retraining the model improved the average sensitivity at a specificity of 97% to 72% from the original 65%. Both the original logistic regression models and locally retrained models were superior to simple billing code count thresholds. DISCUSSION These results show that a previously published algorithm for RA is portable to two external hospitals using different EHR systems, different NLP systems, and different target NLP vocabularies. Retraining the algorithm primarily increased the sensitivity at each site. CONCLUSION Electronic phenotype algorithms allow rapid identification of case populations in multiple sites with little retraining.

Environmental influences on risk for rheumatoid arthritis.

Purpose of reviewTo examine new environmental factors and provide updates on known risk factors for rheumatoid arthritis (RA) in the past 2 years (2006–2008). This review is timely given the expanding information on treatment, pathogenesis and genetic risk factors for RA. Recent findingsHigh consumption of red meat does not increase risk of RA, whereas alcohol intake may be protective. The role of vitamin D and oral contraceptives as modifiers of disease risk remains equivocal. Other factors associated with increased risk of RA include higher birthweight, living in the northeastern United States compared with other regions of the country, and lower socioeconomic status. Duration of breastfeeding is inversely associated with RA risk. Several studies have now demonstrated that anti-citrullinated protein antibody positive RA has a specific association with environmental risk factors such as smoking. SummaryRecent studies have increased our understanding of environmental exposures that modify risk for RA such as smoking and alcohol intake. Other factors such as birthweight, breastfeeding, socioeconomic status and region of birth have also been demonstrated to contribute to risk. ACPA status is associated with specific environmental factors and is therefore important to incorporate into present and future studies.

Anti–citrullinated peptide antibody assays and their role in the diagnosis of rheumatoid arthritis

Increasingly, assays for the detection of anti-citrullinated peptide antibodies (ACPA) are used in RA diagnosis. This review summarizes the biologic basis and development of ACPA assays, available ACPA assays and their performance characteristics, and diagnostic properties of ACPA alone and compared to rheumatoid factor (RF) in early RA. We also review correlations, precision, costs and cost-effectiveness, availability, stability and reproducibility of the available assays. Taken together, data indicate that ACPA has a higher specificity than RF for early RA, good predictive validity, high sensitivity, apparent cost-effectiveness and good stability and reproducibility. Given its superior performance characteristics and increasing availability, ACPA is emerging as the most useful single assay for the diagnosis of RA.

Genetic Basis of Autoantibody Positive and Negative Rheumatoid Arthritis Risk in a Multi-ethnic Cohort Derived from Electronic Health Records

Discovering and following up on genetic associations with complex phenotypes require large patient cohorts. This is particularly true for patient cohorts of diverse ancestry and clinically relevant subsets of disease. The ability to mine the electronic health records (EHRs) of patients followed as part of routine clinical care provides a potential opportunity to efficiently identify affected cases and unaffected controls for appropriate-sized genetic studies. Here, we demonstrate proof-of-concept that it is possible to use EHR data linked with biospecimens to establish a multi-ethnic case-control cohort for genetic research of a complex disease, rheumatoid arthritis (RA). In 1,515 EHR-derived RA cases and 1,480 controls matched for both genetic ancestry and disease-specific autoantibodies (anti-citrullinated protein antibodies [ACPA]), we demonstrate that the odds ratios and aggregate genetic risk score (GRS) of known RA risk alleles measured in individuals of European ancestry within our EHR cohort are nearly identical to those derived from a genome-wide association study (GWAS) of 5,539 autoantibody-positive RA cases and 20,169 controls. We extend this approach to other ethnic groups and identify a large overlap in the GRS among individuals of European, African, East Asian, and Hispanic ancestry. We also demonstrate that the distribution of a GRS based on 28 non-HLA risk alleles in ACPA+ cases partially overlaps with ACPA- subgroup of RA cases. Our study demonstrates that the genetic basis of rheumatoid arthritis risk is similar among cases of diverse ancestry divided into subsets based on ACPA status and emphasizes the utility of linking EHR clinical data with biospecimens for genetic studies.

Traditional cardiovascular risk factors, inflammation and cardiovascular risk in rheumatoid arthritis

Multiple studies demonstrate an increased cardiovascular (CV) risk associated with RA compared with the general population. While part of this risk appears to be mediated by RA-specific factors, such as long-term inflammation, traditional CV comorbidities also play an important role. We review evidence from previous studies of the relationship between RA and traditional CV comorbidities such as dyslipidaemia, obesity, insulin resistance and diabetes, hypertension, cigarette smoking and physical inactivity. We examine the prevalence and consider the effect of inflammation and RA treatments on these risk factors. Finally, we discuss three widely used CV risk estimators, the Framingham Risk Score, Reynolds Risk Score and the Systematic Coronary Risk Evaluation, and their performance in patients with RA. The traditional CV risk factors that appear to differ significantly between RA cases and controls include insulin resistance, abnormal fat distribution, cigarette smoking and lack of physical activity. Dyslipidaemia, diabetes and hypertension may also be elevated in RA; however, the evidence is conflicting. Overall, we found that the majority of information regarding CV risk factors in RA stems from data collected as covariates for studies on CV disease. A gap in knowledge exists regarding detailed information on individual risk factors in RA, their prevalence and modifications that occur as a result of inflammation or treatment. More studies are needed to develop methods for accurate CV risk estimation in RA.

Improving case definition of Crohn's disease and ulcerative colitis in electronic medical records using natural language processing: a novel informatics approach.

Background:Previous studies identifying patients with inflammatory bowel disease using administrative codes have yielded inconsistent results. Our objective was to develop a robust electronic medical record–based model for classification of inflammatory bowel disease leveraging the combination of codified data and information from clinical text notes using natural language processing. Methods:Using the electronic medical records of 2 large academic centers, we created data marts for Crohn’s disease (CD) and ulcerative colitis (UC) comprising patients with ≥1 International Classification of Diseases, 9th edition, code for each disease. We used codified (i.e., International Classification of Diseases, 9th edition codes, electronic prescriptions) and narrative data from clinical notes to develop our classification model. Model development and validation was performed in a training set of 600 randomly selected patients for each disease with medical record review as the gold standard. Logistic regression with the adaptive LASSO penalty was used to select informative variables. Results:We confirmed 399 CD cases (67%) in the CD training set and 378 UC cases (63%) in the UC training set. For both, a combined model including narrative and codified data had better accuracy (area under the curve for CD 0.95; UC 0.94) than models using only disease International Classification of Diseases, 9th edition codes (area under the curve 0.89 for CD; 0.86 for UC). Addition of natural language processing narrative terms to our final model resulted in classification of 6% to 12% more subjects with the same accuracy. Conclusions:Inclusion of narrative concepts identified using natural language processing improves the accuracy of electronic medical records case definition for CD and UC while simultaneously identifying more subjects compared with models using codified data alone.