Phenome-Wide Association Study of Autoantibodies to Citrullinated and Noncitrullinated Epitopes in Rheumatoid Arthritis

Rheumatoid arthritis and changes on spirometry by smoking status in two prospective longitudinal cohorts

OBJECTIVE

To compare longitudinal changes in spirometric measures between patients with rheumatoid arthritis (RA) and non-RA comparators.

METHODS

We analysed longitudinal data from two prospective cohorts: the UK Biobank and COPDGene. Spirometry was conducted at baseline and a second visit after 5-7 years. RA was identified based on self-report and disease-modifying antirheumatic drug use; non-RA comparators reported neither. The primary outcomes were annual changes in the per cent-predicted forced expiratory volume in 1 s (FEV1%) and per cent predicted forced vital capacity (FVC%). Statistical comparisons were performed using multivariable linear regression. The analysis was stratified based on baseline smoking status and the presence of obstructive pattern (FEV1/FVC <0.7).

RESULTS

Among participants who underwent baseline and follow-up spirometry, we identified 233 patients with RA and 37 735 non-RA comparators. Among never-smoking participants without an obstructive pattern, RA was significantly associated with more FEV1% decline (β=-0.49, p=0.04). However, in ever smokers with ≥10 pack-years, those with RA exhibited significantly less FEV1% decline than non-RA comparators (β=0.50, p=0.02). This difference was more pronounced among those with an obstructive pattern at baseline (β=1.12, p=0.01). Results were similar for FEV1/FVC decline. No difference was observed in the annual FVC% change in RA versus non-RA.

CONCLUSIONS

Smokers with RA, especially those with baseline obstructive spirometric patterns, experienced lower FEV1% and FEV1/FVC decline than non-RA comparators. Conversely, never smokers with RA had more FEV1% decline than non-RA comparators. Future studies should investigate potential treatments and the pathogenesis of obstructive lung diseases in smokers with RA.

Multidimensional biomarker approach integrating tumor markers, inflammatory indicators, and disease activity indicators may improve prediction of rheumatoid arthritis-associated interstitial lung disease

INTRODUCTION

Rheumatoid arthritis (RA) often leads to interstitial lung disease (ILD), significantly affecting patient outcomes. This study explored the diagnostic accuracy of a multi-biomarker approach to offer a more efficient and accessible diagnostic strategy for RA-associated ILD (RA-ILD).

METHODS

Patients diagnosed with RA, with or without ILD, at Beijing Tiantan Hospital from October 2019 to October 2023 were analyzed. A total of 125 RA patients were included, with 76 diagnosed with RA-ILD. The study focused on three categories of indicators: tumor markers, inflammatory indicators, and disease activity measures. The heatmap correlation analysis was employed to analyze the correlation among these indicators. Logistic regression was used to determine odds ratios (OR) for indicators linked to RA-ILD risk. Receiver-operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic potential of these indicators for RA-ILD.

RESULTS

The results of logistic regression analysis showed that tumor markers (carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and cytokeratin 19 fragment (CYFRA21-1)), as well as inflammatory indicators (neutrophil, neutrophil-to-lymphocyte ratio (NLR), platelet, C-reactive protein (CRP)) and disease activity measures (disease activity score-28-CRP (DAS28-CRP), rheumatoid factor (RF), and anti-cyclic peptide containing citrulline (anti-CCP)), were significantly associated with RA-ILD. The correlation coefficients among these indicators were relatively low. Notably, the combination indicator 4, which integrated the aforementioned three categories of biomarkers, demonstrated improved diagnostic accuracy with an AUC of 0.857.

CONCLUSION

The study demonstrated that combining tumor markers, inflammatory indicators, and disease activity measures significantly enhanced the prediction of RA-ILD. Key Points • Multidimensional strategy: Integrated tumor markers, inflammatory indicators, and disease activity measures to enhance early detection of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). • Diagnostic accuracy: Employed heatmap correlation and logistic regression, identifying significant associations and improving diagnostic accuracy with a multidimensional biomarker combination. • Superior performance: The combined multidimensional biomarker strategy demonstrated higher diagnostic precision compared to individual or dual-category indicators. • Clinical relevance: Offers a promising, accessible approach for early detection of RA-ILD in clinical settings, potentially improving patient outcomes.

Identification of anti-citrullinated osteopontin antibodies and increased inflammatory response by enhancement of osteopontin binding to fibroblast-like synoviocytes in rheumatoid arthritis

BACKGROUND

Anti-citrullinated protein/peptide antibodies (ACPAs) are present in patients at onset and have important pathogenic roles during the course of rheumatoid arthritis (RA). The characteristics of several molecules recognized by ACPA have been studied in RA, but the positivity rate of autoantibodies against each antigen is not high, and the pathogenic mechanism of each antibody is not fully understood. We investigated the role of anti-citrullinated osteopontin (anti-cit-OPN) antibodies in RA pathogenesis.

METHODS

Enzyme-linked immunosorbent assays on RA patients' sera were used to detect autoantibodies against OPN. Fibroblast-like synoviocytes (FLS) isolated from RA patients were used to test the binding activity and inflammatory response of OPN mediated by anti-cit-OPN antibodies, and their effect was tested using an inflammatory arthritis mouse model immunized with cit-OPN. Anti-cit-OPN antibody positivity and clinical characteristics were investigated in the patients as well.

RESULTS

Using sera from 224 RA patients, anti-cit-OPN antibodies were positive in approximately 44% of RA patients, while approximately 78% of patients were positive for the cyclic citrullinated peptide (CCP2) assay. IgG from patients with anti-cit-OPN antibody increased the binding activity of OPN to FLSs, which further increased matrix metalloproteinase and interleukin-6 production in TNF-stimulated FLSs. Mice immunized with cit-OPN antibodies experienced severe arthritis. Anti-cit-OPN antibodies in RA patients decreased the drug survival rate of tumor necrosis factor (TNF) inhibitors, while it did not decrease that of CTLA4-Ig.

CONCLUSIONS

Anti-cit-OPN antibodies were detected in patients with RA. IgG from patients with anti-cit-OPN antibodies aggravated RA, and anti-cit-OPN antibody was a marker of reduced the survival rate of TNF inhibitors in RA patients.

Autoantibodies against citrullinated and native proteins and prediction of rheumatoid arthritis-associated interstitial lung disease: A nested case-control study

Background

To identify fine specificity anti-citrullinated protein antibodies (ACPA) associated with incident rheumatoid arthritis-associated interstitial lung disease (RA-ILD).

Methods

This nested case-control study within the Brigham RA Sequential Study matched incident RA-ILD cases to RA-noILD controls on time of blood collection, age, sex, RA duration, and rheumatoid factor status. A multiplex assay measured ACPA and anti-native protein antibodies from stored serum prior to RA-ILD onset. Logistic regression models calculated odds ratios (OR) with 95% confidence intervals (CI) for RA-ILD, adjusting for prospectively-collected covariates. We estimated optimism-corrected area under the curves (AUC) using internal validation. Model coefficients generated a risk score for RA-ILD.

Findings

We analyzed 84 incident RA-ILD cases (mean age 67 years, 77% female, 90% White) and 233 RA-noILD controls (mean age 66 years, 80% female, 94% White). We identified six fine specificity antibodies that were associated with RA-ILD. The antibody isotypes and targeted proteins were: IgA2 to citrullinated histone 4 (OR 0.08 per log-transformed unit, 95% CI 0.03-0.22), IgA2 to citrullinated histone 2A (OR 4.03, 95% CI 2.03-8.00), IgG to cyclic citrullinated filaggrin (OR 3.47, 95% CI 1.71-7.01), IgA2 to native cyclic histone 2A (OR 5.52, 95% CI 2.38-12.78), IgA2 to native histone 2A (OR 4.60, 95% CI 2.18-9.74), and IgG to native cyclic filaggrin (OR 2.53, 95% CI 1.47-4.34). These six antibodies predicted RA-ILD risk better than all clinical factors combined (optimism-corrected AUC=0·84 versus 0·73). We developed a risk score for RA-ILD combining these antibodies with the clinical factors (smoking, disease activity, glucocorticoid use, obesity). At 50% predicted RA-ILD probability, the risk scores both without (score=2·6) and with (score=5·9) biomarkers achieved specificity ≥93% for RA-ILD.

Interpretation

Specific ACPA and anti-native protein antibodies improve RA-ILD prediction. These findings implicate synovial protein antibodies in the pathogenesis of RA-ILD and suggest clinical utility in predicting RA-ILD once validated in external studies.

Funding

National Institutes of Health.

Stratification of rheumatoid arthritis cohort using Ayurveda based deep phenotyping approach identifies novel genes in a GWAS

Background and aim

Genome wide association studies have scaled up both in terms of sample size and range of complex disorders investigated, but these have explained relatively little phenotypic variance. Of the several reasons, phenotypic heterogeneity seems to be a likely contributor for missing out genetic associations of large effects. Ayurveda, the traditional Indian system of medicine is one such tool which adopts a holistic deep phenotyping approach and classifies individuals based on their body constitution/prakriti. We hypothesized that Ayurveda based phenotypic stratification of healthy and diseased individuals will allow us to achieve much desired homogeneous cohorts which would facilitate detection of genetic association of large effects. In this proof of concept study, we performed a genome wide association testing of clinically diagnosed rheumatoid arthritis patients and healthy controls, who were re-phenotyped into Vata, Pitta and Kapha predominant prakriti sub-groups.

Experimental procedure

Genotypes of rheumatoid arthritis cases (Vata = 49; Pitta = 117; Kapha = 78) and controls (Vata = 33; Pitta = 175; Kapha = 85) were retrieved from the total genotype data, used in a recent genome-wide association study performed in our laboratory. A total of 528461 SNPs were included after quality control. Prakriti-wise genome-wide association analysis was employed.

Results and conclusion

This study identified (i) prakriti-specific novel disease risk genes of high effect sizes; (ii) putative candidates of novel therapeutic potential; and (iii) a good correlation between genetic findings and clinical knowledge in Ayurveda. Adopting Ayurveda based deep phenotyping may facilitate explaining hitherto undiscovered heritability in complex traits and may propel much needed progress in personalized medicine.

Interaction of obesity polygenic score with lifestyle risk factors in an electronic health record biobank

BACKGROUND

Genetic and lifestyle factors have considerable effects on obesity and related diseases, yet their effects in a clinical cohort are unknown. This study in a patient biobank examined associations of a BMI polygenic risk score (PRS), and its interactions with lifestyle risk factors, with clinically measured BMI and clinical phenotypes.

METHODS

The Mass General Brigham (MGB) Biobank is a hospital-based cohort with electronic health record, genetic, and lifestyle data. A PRS for obesity was generated using 97 genetic variants for BMI. An obesity lifestyle risk index using survey responses to obesogenic lifestyle risk factors (alcohol, education, exercise, sleep, smoking, and shift work) was used to dichotomize the cohort into high and low obesogenic index based on the population median. Height and weight were measured at a clinical visit. Multivariable linear cross-sectional associations of the PRS with BMI and interactions with the obesity lifestyle risk index were conducted. In phenome-wide association analyses (PheWAS), similar logistic models were conducted for 675 disease outcomes derived from billing codes.

RESULTS

Thirty-three thousand five hundred eleven patients were analyzed (53.1% female; age 60.0 years; BMI 28.3 kg/m²), of which 17,040 completed the lifestyle survey (57.5% female; age: 60.2; BMI: 28.1 (6.2) kg/m²). Each standard deviation increment in the PRS was associated with 0.83 kg/m² unit increase in BMI (95% confidence interval (CI) =0.76, 0.90). There was an interaction between the obesity PRS and obesity lifestyle risk index on BMI. The difference in BMI between those with a high and low obesogenic index was 3.18 kg/m² in patients in the highest decile of PRS, whereas that difference was only 1.55 kg/m² in patients in the lowest decile of PRS. In PheWAS, the obesity PRS was associated with 40 diseases spanning endocrine/metabolic, circulatory, and 8 other disease groups. No interactions were evident between the PRS and the index on disease outcomes.

CONCLUSIONS

In this hospital-based clinical biobank, obesity risk conferred by common genetic variants was associated with elevated BMI and this risk was attenuated by a healthier patient lifestyle. Continued consideration of the role of lifestyle in the context of genetic predisposition in healthcare settings is necessary to quantify the extent to which modifiable lifestyle risk factors may moderate genetic predisposition and inform clinical action to achieve personalized medicine.

Disorders of Fibrinogen and Fibrinolysis

Fibrinogen plays a fundamental role in coagulation through its support for platelet aggregation and its conversion to fibrin. Fibrin stabilizes clots and serves as a scaffold and immune effector before being broken down by the fibrinolytic system. Given its importance, abnormalities in fibrin(ogen) and fibrinolysis result in a variety of disorders with hemorrhagic and thrombotic manifestations. This review summarizes (i) the basic elements of fibrin(ogen) and its role in coagulation and the fibrinolytic system; (ii) the laboratory evaluation for fibrin(ogen) disorders, including the use of global fibrinolysis assays; and (iii) the management of congenital and acquired disorders of fibrinogen and fibrinolysis.

Using Phecodes for Research with the Electronic Health Record: From PheWAS to PheRS

Electronic health records (EHRs) are a rich source of data for researchers, but extracting meaningful information out of this highly complex data source is challenging. Phecodes represent one strategy for defining phenotypes for research using EHR data. They are a high-throughput phenotyping tool based on ICD (International Classification of Diseases) codes that can be used to rapidly define the case/control status of thousands of clinically meaningful diseases and conditions. Phecodes were originally developed to conduct phenome-wide association studies to scan for phenotypic associations with common genetic variants. Since then, phecodes have been used to support a wide range of EHR-based phenotyping methods, including the phenotype risk score. This review aims to comprehensively describe the development, validation, and applications of phecodes and suggest some future directions for phecodes and high-throughput phenotyping.

Methodology in phenome-wide association studies: a systematic review

Phenome-wide association study (PheWAS) has been increasingly used to identify novel genetic associations across a wide spectrum of phenotypes. This systematic review aims to summarise the PheWAS methodology, discuss the advantages and challenges of PheWAS, and provide potential implications for future PheWAS studies. Medical Literature Analysis and Retrieval System Online (MEDLINE) and Excerpta Medica Database (EMBASE) databases were searched to identify all published PheWAS studies up until 24 April 2021. The PheWAS methodology incorporating how to perform PheWAS analysis and which software/tool could be used, were summarised based on the extracted information. A total of 1035 studies were identified and 195 eligible articles were finally included. Among them, 137 (77.0%) contained 10 000 or more study participants, 164 (92.1%) defined the phenome based on electronic medical records data, 140 (78.7%) used genetic variants as predictors, and 73 (41.0%) conducted replication analysis to validate PheWAS findings and almost all of them (94.5%) received consistent results. The methodology applied in these PheWAS studies was dissected into several critical steps, including quality control of the phenome, selecting predictors, phenotyping, statistical analysis, interpretation and visualisation of PheWAS results, and the workflow for performing a PheWAS was established with detailed instructions on each step. This study provides a comprehensive overview of PheWAS methodology to help practitioners achieve a better understanding of the PheWAS design, to detect understudied or overstudied outcomes, and to direct their research by applying the most appropriate software and online tools for their study data structure.

Sleep health, diseases, and pain syndromes: findings from an electronic health record biobank

STUDY OBJECTIVES

Implementation of electronic health record biobanks has facilitated linkage between clinical and questionnaire data and enabled assessments of relationships between sleep health and diseases in phenome-wide association studies (PheWAS). In the Mass General Brigham Biobank, a large health system-based study, we aimed to systematically catalog associations between time in bed, sleep timing, and weekly variability with clinical phenotypes derived from ICD-9/10 codes.

METHODS

Self-reported habitual bed and wake times were used to derive variables: short (<7 hours) and long (≥9 hours) time in bed, sleep midpoint, social jetlag, and sleep debt. Logistic regression and Cox proportional hazards models were used to test cross-sectional and prospective associations, respectively, adjusted for age, gender, race/ethnicity, and employment status and further adjusted for body mass index.

RESULTS

In cross-sectional analysis (n = 34,651), sleep variable associations were most notable for circulatory system, mental disorders, and endocrine/metabolic phenotypes. We observed the strongest associations for short time in bed with obesity, for long time in bed and sleep midpoint with major depressive disorder, for social jetlag with hypercholesterolemia, and for sleep debt with acne. In prospective analysis (n = 24,065), we observed short time in bed associations with higher incidence of acute pain and later sleep midpoint and higher sleep debt and social jetlag associations with higher incidence of major depressive disorder.

CONCLUSIONS

Our analysis reinforced that sleep health is a multidimensional construct, corroborated robust known findings from traditional cohort studies, and supported the application of PheWAS as a promising tool for advancing sleep research. Considering the exploratory nature of PheWAS, careful interrogation of novel findings is imperative.

Rheumatoid arthritis related interstitial lung disease

INTRODUCTION

Interstitial lung disease (ILD) represents a frequent extra-articular manifestation of rheumatoid arthritis (RA) deeply impacting both quality of life and overall prognosis. Areas covered: A literature search was performed including PubMed, Embase, Scopus, and Web of Science. Many retrospective studies investigated the possible risk factors for RA-related ILD (RA-ILD), aiming to identify patients at risk. Among them, males, smokers, positivity of anti-citrullinated peptide antibodies have been associated with RA-ILD, such as some genetic haplotypes. Usual interstitial pneumonia is the histologic and radiologic pattern most frequently observed, followed by nonspecific interstitial pneumonia. Since lung involvement can represent the RA onset, an early differential diagnosis with idiopathic interstitial pneumonia can be difficult or sometimes impossible. High-resolution computed tomography represents the gold standard for ILD diagnosis, while multidisciplinary discussion should be required to assess disease staging, severity and progression.  Expert opinion: Management of RA-ILD patients is challenging due to the lack of evidence-based data regarding both assessment and treatment. Moreover, the high variability of clinical presentation and evolution makes it difficult to establish the correct therapeutic strategy. Currently, multidisciplinary approach, including at least rheumatologists, pulmonologists, and radiologists, is desirable to define therapy and follow-up strategies.

Impact of ICD10 and secular changes on electronic medical record rheumatoid arthritis algorithms

OBJECTIVE

The objective of this study was to compare the performance of an RA algorithm developed and trained in 2010 utilizing natural language processing and machine learning, using updated data containing ICD10, new RA treatments, and a new electronic medical records (EMR) system.

METHODS

We extracted data from subjects with ≥1 RA International Classification of Diseases (ICD) codes from the EMR of two large academic centres to create a data mart. Gold standard RA cases were identified from reviewing a random 200 subjects from the data mart, and a random 100 subjects who only have RA ICD10 codes. We compared the performance of the following algorithms using the original 2010 data with updated data: (i) a published 2010 RA algorithm; (ii) updated algorithm, incorporating ICD10 RA codes and new DMARDs; and (iii) published algorithm using ICD codes only, ICD RA code ≥3.

RESULTS

The gold standard RA cases had mean age 65.5 years, 78.7% female, 74.1% RF or antibodies to cyclic citrullinated peptide (anti-CCP) positive. The positive predictive value (PPV) for ≥3 RA ICD was 54%, compared with 56% in 2010. At a specificity of 95%, the PPV of the 2010 algorithm and the updated version were both 91%, compared with 94% (95% CI: 91, 96%) in 2010. In subjects with ICD10 data only, the PPV for the updated 2010 RA algorithm was 93%.

CONCLUSION

The 2010 RA algorithm validated with the updated data with similar performance characteristics as the 2010 data. While the 2010 algorithm continued to perform better than the rule-based approach, the PPV of the latter also remained stable over time.

Rheumatoid arthritis-associated interstitial lung disease: Current update on prevalence, risk factors, and pharmacologic treatment

Purpose of review

Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is one of the most serious extra-articular RA manifestations. RA-ILD is associated with worse physical function, lower quality of life, and increased mortality. RA-ILD is comprised of heterogeneous subtypes characterized by inflammation and fibrosis. Diagnosis can be difficult since the presentation of RA-ILD is characterized by non-specific symptoms and imaging findings. Management of RA-ILD is also challenging due to difficulty in precisely measuring pulmonary disease activity and response to treatment in patients who may also have articular inflammation. We provide a current overview of RA-ILD focusing on prevalence, risk factors, and treatment.

Recent findings

Research interest in RA-ILD has increased in recent years. Some studies suggest that RA-ILD prevalence may be increasing; this may be due to underlying biologic drivers or increases in imaging and recognition. Novel RA-ILD risk factors include the MUC5B promotor variant, articular disease activity, autoantibodies, and biomarkers of damaged pulmonary parenchyma. Treatment should focus on controlling RA disease activity, which emerging data suggest may reduce RA-ILD risk. Immunomodulatory and antifibrotic drugs may also treat RA-ILD.

Summary

RA-ILD is an underrecognized and serious manifestation of RA, but important progress is being made in identifying risk factors and treatment.

Phenome-wide examination of comorbidity burden and multiple sclerosis disease severity

Objective

We assessed the comorbidity burden associated with multiple sclerosis (MS) severity by performing a phenome-wide association study (PheWAS).

Methods

We conducted a PheWAS in 2 independent cohorts: a discovery (Boston, United States; 1993–2014) and extension cohort (British Columbia, Canada; 1991–2008). We included adults with MS, ≥1 Expanded Disability Status Scale (EDSS) score, and ≥1 International Classification of Diseases (ICD) code other than MS. We calculated the Multiple Sclerosis Severity Score (MSSS) using the EDSS. We mapped ICD codes into PheCodes (phenotypes), using a published system with each PheCode representing a unique medical condition. Association between the MSSS and the presence of each condition was assessed using logistic regression adjusted for covariates.

Results

The discovery and extension cohorts included 3,439 and 4,876 participants, respectively. After Bonferroni correction and covariate adjustments, a higher MSSS was associated with 37 coexisting conditions in the discovery cohort. Subsequently, 16 conditions, including genitourinary, infectious, metabolic, epilepsy, and movement disorders, met the reporting criteria, reaching the Bonferroni threshold of significance with the same direction of effect in the discovery and extension cohort. Notably, benign neoplasm of the skin was inversely associated with the MSSS.

Conclusion

The phenome-wide approach enabled a systematic interrogation of the comorbidity burden and highlighted clinically relevant medical conditions associated with MS severity (beyond MS-specific consequences) and defines a roadmap for comprehensive investigation of comorbidities in chronic neurologic diseases. Further prospective investigation of the bidirectional relationship between disability and comorbidities could inform the individualized patient management.

An analytic framework for exploring sampling and observation process biases in genome and phenome-wide association studies using electronic health records

Large-scale association analyses based on observational health care databases such as electronic health records have been a topic of increasing interest in the scientific community. However, challenges due to nonprobability sampling and phenotype misclassification associated with the use of these data sources are often ignored in standard analyses. The extent of the bias introduced by ignoring these factors is not well-characterized. In this paper, we develop an analytic framework for characterizing the bias expected in disease-gene association studies based on electronic health records when disease status misclassification and the sampling mechanism are ignored. Through a sensitivity analysis approach, this framework can be used to obtain plausible values for parameters of interest given summary results from standard analysis. We develop an online tool for performing this sensitivity analysis. Simulations demonstrate promising properties of the proposed method. We apply our approach to study bias in disease-gene association studies using electronic health record data from the Michigan Genomics Initiative, a longitudinal biorepository effort within The University Michigan health system.

The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities

Biobanks linked to electronic health records provide rich resources for health-related research. With improvements in administrative and informatics infrastructure, the availability and utility of data from biobanks have dramatically increased. In this paper, we first aim to characterize the current landscape of available biobanks and to describe specific biobanks, including their place of origin, size, and data types. The development and accessibility of large-scale biorepositories provide the opportunity to accelerate agnostic searches, expedite discoveries, and conduct hypothesis-generating studies of disease-treatment, disease-exposure, and disease-gene associations. Rather than designing and implementing a single study focused on a few targeted hypotheses, researchers can potentially use biobanks' existing resources to answer an expanded selection of exploratory questions as quickly as they can analyze them. However, there are many obvious and subtle challenges with the design and analysis of biobank-based studies. Our second aim is to discuss statistical issues related to biobank research such as study design, sampling strategy, phenotype identification, and missing data. We focus our discussion on biobanks that are linked to electronic health records. Some of the analytic issues are illustrated using data from the Michigan Genomics Initiative and UK Biobank, two biobanks with two different recruitment mechanisms. We summarize the current body of literature for addressing these challenges and discuss some standing open problems. This work complements and extends recent reviews about biobank-based research and serves as a resource catalog with analytical and practical guidance for statisticians, epidemiologists, and other medical researchers pursuing research using biobanks.

Association of rheumatoid arthritis-related autoantibodies with pulmonary function test abnormalities in a rheumatoid arthritis registry

INTRODUCTION

We investigated whether rheumatoid arthritis (RA)-related autoantibodies were associated with abnormalities on pulmonary function tests (PFTs).

METHODS

We studied RA serostatus and PFT abnormalities within a RA registry. RA serostatus was assessed by research assays for cyclic citrullinated peptide (CCP) and rheumatoid factor (RF). Outcomes were abnormalities on clinically indicated PFTs, including restriction, obstruction, and diffusion abnormality. Logistic regression was used to obtain ORs and 95% CIs for the PFT abnormalities by RA serologic phenotypes independent of lifestyle and RA characteristics.

RESULTS

Among 1272 analyzed subjects, mean age was 56.3 years (SD 14.1), 82.2% were female, and 69.5% were seropositive. There were 100 subjects with abnormal PFTs. Compared with seronegativity, seropositivity was associated with increased odds of any PFT abnormality (multivariable OR 2.29, 95% CI 1.30-4.03). When analyzing type of PFT abnormality, seropositivity was also associated with restriction, obstruction, and diffusion abnormalities; multivariable ORs were 2.48 (95% CI 1.26-4.87), 3.12 (95% CI 1.28-7.61), and 2.30 (95% CI 1.09-4.83), respectively. When analyzing by CCP and RF status, the associations were stronger for RF+ than for CCP+ (any PFT abnormality OR 1.99, 95% CI 1.21-3.27 for RF+ vs. RF-; OR 1.67, 95% CI 1.03-2.69 for CCP+ vs. CCP-) with a dose effect of higher RF titer increasing odds for each PFT abnormality (p for trend < 0.05).

CONCLUSIONS

Seropositive RA patients had two-fold increased risk for abnormalities on PFTs performed for clinical indications compared with seronegative RA. Patients with seropositive RA, particularly those with high-titer RF positivity, may be more likely to have obstructive and restrictive abnormalities, independent of smoking.Key points• Due to the known excess pulmonary morbidity/mortality in RA, we studied the relationship of rheumatoid arthritis (RA)-related autoantibodies with pulmonary function test (PFT) abnormalities using a large RA registry.• We evaluated whether presence and levels of cyclic citrullinated peptide (CCP) and rheumatoid factor (RF) were associated with restriction, obstruction, and diffusion abnormalities on PFTs among 1272 subjects with RA.• Seropositivity was associated with two-fold increased risk for any PFT abnormality, independent of confounders including smoking. Higher titers of RF conferred greatest risk for all PFT outcomes: obstruction, restriction, and diffusion abnormality.• These results provide evidence that patients with RA should be closely monitored for pulmonary involvement, particularly those with high-titer RF seropositivity.

Phenome-Wide Association Studies Uncover a Novel Association of Increased Atrial Fibrillation in Male Patients With Systemic Lupus Erythematosus

OBJECTIVE

Phenome-wide association studies (PheWAS) scan across billing codes in the electronic health record (EHR) and re-purpose clinical EHR data for research. In this study, we examined whether PheWAS could function as an EHR-based discovery tool for systemic lupus erythematosus (SLE) and identified novel clinical associations in male versus female patients with SLE.

METHODS

We used a de-identified version of the Vanderbilt University Medical Center EHR, which includes more than 2.8 million subjects. We performed EHR-based PheWAS to compare SLE patients with age-, sex-, and race-matched control subjects and to compare male SLE patients with female SLE patients, controlling for multiple testing using a false discovery rate (FDR) P value of 0.05.

RESULTS

We identified 1,097 patients with SLE and 5,735 matched control subjects. In a comparison of patients with SLE and matched controls, SLE patients were shown to be more likely to have International Classification of Diseases, Ninth Revision codes related to the SLE disease criteria. In the PheWAS of male versus female SLE patients, with adjustment for age and race, male patients were shown to be more likely to have atrial fibrillation (odds ratio 4.50, false discovery rate P = 3.23 × 10^-3 ). Chart review confirmed atrial fibrillation, with the majority of patients developing atrial fibrillation after the SLE diagnosis and having multiple risk factors for atrial fibrillation. After adjustment for age, sex, race, and coronary artery disease, SLE disease status was shown to be significantly associated with atrial fibrillation (P = 0.002).

CONCLUSION

Using PheWAS to compare male and female patients with SLE, we identified a novel association of an increased incidence of atrial fibrillation in male patients. SLE disease status was shown to be independently associated with atrial fibrillation, even after adjustment for age, sex, race, and coronary artery disease. These results demonstrate the utility of PheWAS as an EHR-based discovery tool for SLE.

Phenome-wide association study identifies dsDNA as a driver of major organ involvement in systemic lupus erythematosus

In systemic lupus erythematosus (SLE), dsDNA antibodies are associated with renal disease. Less is known about comorbidities in patients without dsDNA or other autoantibodies. Using an electronic health record (EHR) SLE cohort, we employed a phenome-wide association study (PheWAS) that scans across billing codes to compare comorbidities in SLE patients with and without autoantibodies. We used our validated algorithm to identify SLE subjects. Autoantibody status was defined as ever positive for dsDNA, RNP, Smith, SSA and SSB. PheWAS was performed in antibody positive vs. negative SLE patients adjusting for age and race and using a false discovery rate of 0.05. We identified 1097 SLE subjects. In the PheWAS of dsDNA positive vs. negative subjects, dsDNA positive subjects were more likely to have nephritis ( p = 2.33 × 10^-9) and renal failure ( p = 1.85 × 10^-5). After adjusting for sex, race, age and other autoantibodies, dsDNA was independently associated with nephritis and chronic kidney disease. Those patients negative for dsDNA, RNP, SSA and SSB negative subjects were all more likely to have billing codes for sleep, pain and mood disorders. PheWAS uncovered a hierarchy within SLE-specific autoantibodies with dsDNA having the greatest impact on major organ involvement.

Association Between Anti-Citrullinated Fibrinogen Antibodies and Coronary Artery Disease in Rheumatoid Arthritis

OBJECTIVE

Antibodies against citrullinated fibrinogen (anti-Cit-fibrinogen) have been implicated in rheumatoid arthritis (RA) and associated with cardiovascular risk in RA. The objective of this study was to examine the association between anti-Cit-fibrinogens and coronary artery disease (CAD) outcomes.

METHODS

We performed the study in an RA cohort based in a large academic institution linked with electronic medical record data containing information on CAD outcomes from medical record review. Using a published bead-based assay method, we measured 10 types of anti-Cit-fibrinogens. We applied a score test to determine the association between the anti-Cit-fibrinogens as a group with CAD outcomes. Principal components analysis (PCA) was performed to assess whether the anti-Cit-fibrinogens clustered into groups. Each group was then additionally tested for association with CAD. Sensitivity analyses were also performed using a published International Classification of Disease, Ninth Revision code group for ischemic heart disease (IHD) as the outcome.

RESULTS

We studied 1,006 RA subjects (mean ± SD age 61.0 ± 13.0 years; 72.2% anti-cyclic citrullinated peptide positive). As a group, anti-Cit-fibrinogen was associated with CAD (P = 1.1 × 10^-4 ). From the PCA analysis, we observed 3 main groups, of which only 1 group, containing 7 of the 10 anti-Cit-fibrinogens, was significantly associated with CAD outcomes (P = 0.015). In the sensitivity analysis, all anti-Cit-fibrinogens as a group remained significantly associated with IHD (P = 2.9 × 10^-4 ).

CONCLUSION

Anti-Cit-fibrinogen antibodies as a group were associated with CAD outcomes in our RA cohort, with the strongest signal for association arising from a subset of the autoantibodies.

Phenome-wide association study identifies marked increased in burden of comorbidities in African Americans with systemic lupus erythematosus

Background

African Americans with systemic lupus erythematosus (SLE) have increased renal disease compared to Caucasians, but differences in other comorbidities have not been well-described. We used an electronic health record (EHR) technique to test for differences in comorbidities in African Americans compared to Caucasians with SLE.

Methods

We used a de-identified EHR with 2.8 million subjects to identify SLE cases using a validated algorithm. We performed phenome-wide association studies (PheWAS) comparing African American to Caucasian SLE cases and African American SLE cases to matched non-SLE controls. Controls were age, sex, and race matched to SLE cases. For multiple testing, a false discovery rate (FDR) p value of 0.05 was used.

Results

We identified 270 African Americans and 715 Caucasians with SLE and 1425 matched African American controls. Compared to Caucasians with SLE adjusting for age and sex, African Americans with SLE had more comorbidities in every organ system. The most striking included hypertension odds ratio (OR) = 4.25, FDR p = 5.49 × 10^{− 15}; renal dialysis OR = 10.90, FDR p = 8.75 × 10^{− 14}; and pneumonia OR = 3.57, FDR p = 2.32 × 10^{− 8}. Compared to the African American matched controls without SLE, African Americans with SLE were more likely to have comorbidities in every organ system. The most significant codes were renal and cardiac, and included renal failure (OR = 9.55, FDR p = 2.26 × 10^{− 40}) and hypertensive heart and renal disease (OR = 8.08, FDR p = 1.78 × 10^{− 22}). Adjusting for race, age, and sex in a model including both African American and Caucasian SLE cases and controls, SLE was independently associated with renal, cardiovascular, and infectious diseases (all p < 0.01).

Conclusions

African Americans with SLE have an increased comorbidity burden compared to Caucasians with SLE and matched controls. This increase in comorbidities in African Americans with SLE highlights the need to monitor for cardiovascular and infectious complications.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1561-8) contains supplementary material, which is available to authorized users.

Rheumatoid arthritis and risk of chronic obstructive pulmonary disease or asthma among women: A marginal structural model analysis in the Nurses' Health Study

OBJECTIVE

We investigated whether RA increases risk for chronic obstructive pulmonary disease (COPD) or asthma independent of factors occurring before RA onset or mediating these respiratory morbidities after diagnosis, such as cigarette smoking.

METHODS

Within the prospective Nurses' Health Study (n = 121,701 women; 1976-2014), we identified an incident RA cohort and matched each woman with RA to 10 comparators without RA by age and year at index date of RA diagnosis, excluding women with COPD or asthma at baseline. Data were obtained through biennial questionnaires and medical records. We used marginal structural models to determine the independent effect of RA on incident COPD or asthma adjusting for confounders and time-varying mediators through inverse probability weighting.

RESULTS

We identified 843 women with RA, matched to 8,399 comparators without RA. Mean age was 59.8 years and mean follow-up after index date was 18.6 years (SD = 9.0) for women with RA, and 18.8 years (SD = 9.5) for comparators. We identified 68 (8.1%) incident COPD and 40 (4.7%) asthma cases among women with RA, and 459 (5.5%) COPD and 268 (3.2%) asthma cases among comparators. RA was associated with increased risk of COPD (HR = 1.52, 95% CI: 1.17-1.97) and asthma (HR = 1.55, 95% CI: 1.11-2.16) compared to comparators adjusted for the matching factors of age and calendar year at index date. After further adjustment for confounders and time-varying mediators occurring after index date, including smoking, RA was significantly associated with COPD (HR = 1.68, 95% CI: 1.36-2.07), but not asthma (HR = 1.11, 95% CI: 0.59-2.09) compared to non-RA comparators. Women with seropositive RA (HR = 1.60, 95% CI: 1.17-2.19) and seronegative RA (HR = 1.62, 95% CI: 1.09-2.40) had similar increased risk for COPD compared to non-RA comparators.

CONCLUSION

In this prospective cohort study, RA was associated with increased risk for incident COPD, independent of lifestyle confounders and mediators after diagnosis, including smoking.

Current Scope and Challenges in Phenome-Wide Association Studies

PURPOSE OF REVIEW

Over many decades, researchers have been designing studies to investigate the relationship between genotypes and phenotypes to gain an understanding about the effect of genetics on disease. Recently, a high-throughput approach called phenome-wide associations studies (PheWAS) have been extensively used to identify associations between genetic variants and many diseases and traits simultaneously. In this review, we describe the value of PheWAS along with methodological issues and challenges in interpretation for current applications of PheWAS.

RECENT FINDINGS

PheWAS have uncovered a paradigm to identify new associations for genetic loci across many diseases. The application of PheWAS have been effective with phenotype data from electronic health records, epidemiological studies, and clinical trials data.

SUMMARY

The key strength of a PheWAS is to identify the association of one or more genetic variants with multiple phenotypes, which can showcase interconnections among the phenotypes due to shared genetic associations. While the PheWAS approach appears promising, there are a number of challenges that need to be addressed to provide additional robustness to PheWAS findings.

Phenotype validation in electronic health records based genetic association studies

The linkage between electronic health records (EHRs) and genotype data makes it plausible to study the genetic susceptibility of a wide range of disease phenotypes. Despite that EHR-derived phenotype data are subjected to misclassification, it has been shown useful for discovering susceptible genes, particularly in the setting of phenome-wide association studies (PheWAS). It is essential to characterize discovered associations using gold standard phenotype data by chart review. In this work, we propose a genotype stratified case-control sampling strategy to select subjects for phenotype validation. We develop a closed-form maximum-likelihood estimator for the odds ratio parameters and a score statistic for testing genetic association using the combined validated and error-prone EHR-derived phenotype data, and assess the extent of power improvement provided by this approach. Compared with case-control sampling based only on EHR-derived phenotype data, our genotype stratified strategy maintains nominal type I error rates, and result in higher power for detecting associations. It also corrects the bias in the odds ratio parameter estimates, and reduces the corresponding variance especially when the minor allele frequency is small.