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 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

CD19 + CD21lo/neg cells are increased in systemic sclerosis-associated interstitial lung disease

Interstitial lung disease (ILD) represents a significant cause of morbidity and mortality in systemic sclerosis (SSc). The purpose of this study was to examine recirculating lymphocytes from SSc patients for potential biomarkers of interstitial lung disease (ILD). Peripheral blood mononuclear cells (PBMCs) were isolated from patients with SSc and healthy controls enrolled in the Vanderbilt University Myositis and Scleroderma Treatment Initiative Center cohort between 9/2017-6/2019. Clinical phenotyping was performed by chart abstraction. Immunophenotyping was performed using both mass cytometry and fluorescence cytometry combined with t-distributed stochastic neighbor embedding analysis and traditional biaxial gating. This study included 34 patients with SSc-ILD, 14 patients without SSc-ILD, and 25 healthy controls. CD2

IgG4-Related Disease Presenting as Recurrent Mastoiditis With Central Nervous System Involvement

We report a case of a 43-year-old female who presented with right ear fullness and otorrhea. She was initially diagnosed with mastoiditis that was not responsive to multiple courses of antibiotics and steroids. She was then diagnosed with refractory inflammatory pseudotumor, and subsequent treatments included several mastoidectomies, further steroids, and radiation therapy. The patient went on to develop mastoiditis on the contralateral side as well as central nervous system involvement with headaches and right-sided facial paresthesias. Reexamination of the mastoid tissue revealed a significantly increased number of IgG4-positive cells, suggesting a diagnosis of IgG4-related disease. The patient improved clinically and radiographically with rituximab and was able to taper off azathioprine and prednisone. IgG4-related disease should be considered in patients with otologic symptoms and be on the differential diagnosis in patients with inflammatory pseudotumor. Staining for IgG and IgG4 is essential to ensure a prompt diagnosis and treatment

Rheumatologists\u27 perception of systemic lupus erythematosus quality indicators: significant interest and perceived barriers.

Differences in quality of care may contribute to health disparities in systemic lupus erythematosus (SLE). Studies show low physician adherence rates to the SLE quality indicators but do not assess physician perception of SLE quality indicators or quality improvement. Using a cross-sectional survey of rheumatologists in the southeastern USA, we assessed the perception and involvement of rheumatologists in quality improvement and the SLE quality indicators. Using electronic mail, an online survey of 32 questions was delivered to 568 rheumatologists. With a response rate of 19% (n = 106), the majority of participants were male, Caucasian, with over 20 years of experience, and seeing adult patients in an academic setting. Participants had a positive perception toward quality improvement (81%) with a majority responding that the SLE quality indicators would significantly impact quality of care (54%). While 66% of respondents were familiar with the SLE quality indicators, only 18% of respondents reported using them in everyday practice. The most commonly reported barrier to involvement in quality improvement and the SLE quality indicators was time. Rheumatologists had a positive perception of the SLE quality indicators and agreed that use of the quality indicators could improve quality of care in SLE; however, they identified time as a barrier to implementation. Future studies should investigate methods to increase use of the SLE quality indicators

Phenome-wide association studies uncover hierarchy of autoantibodies in systemic lupus erythematosus

Background Systemic lupus erythematosus (SLE) is a heterogeneous disease with diverse presentations. dsDNA antibodies associate with renal disease. Less is known about comorbidities in SLE patients without dsDNA antibodies. Using a large electronic health record (EHR) cohort, we sought to identify comorbidities that associate with dsDNA status. We used a technique that scans across EHR billing codes called phenome-wide association study (PheWAS) to compare SLE patients with and without dsDNA antibodies. We also evaluated the relative importance of SLE specific autoantibodies on SLE criteria. Methods We used our validated SLE algorithm of ≥4 counts of the SLE ICD-9 code and ANA positive ≥1:160 while excluding dermatomyositis and systemic sclerosis ICD-9 codes with a positive predictive value of 94% and a sensitivity of 86%. We identified SLE cases in a de-identified EHR that contains over 2.8 million subjects. Autoantibody status was defined as ever positive for dsDNA, RNP, Smith, SSA, and SSB. PheWAS was performed in dsDNA positive vs negative SLE patients using logistic regression adjusting for current age and race. For multiple testing, a false discovery rate (FDR) p of 0.05 was used. We also performed logistic regression to assess the impact of autoantibodies, age, sex, and race on SLE criteria. Results We identified 1097 SLE subjects. As expected, dsDNA positive subjects, compared to dsDNA negative, were more likely to have renal codes including nephritis (OR=4.60, FDR p=2.33 × 10-9), renal failure (OR=2.30, FDR p=1.85 × 10-5), and end stage renal disease (OR=2.63, FDR p=0.01). After adjusting for sex, race, age, and other autoantibodies, dsDNA was independently associated with nephritis (p=1.98 × 10-6) and chronic kidney disease (p=0.001) and also associated, along with SSB, with serositis (p=0.01) and hematologic criteria (p=0.001) (figure 1). dsDNA negative subjects were more likely to have codes for sleep, pain, and mood disorders. Conclusion Using PheWAS, we uncovered a hierarchy within SLE specific autoantibodies where dsDNA, compared to other autoantibodies, was a powerful predictor of major organ involvement in SL

Phenome-wide association studies uncover a novel association of increased atrial fibrillation in males 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. We examined if PheWAS could function as an EHR discovery tool for SLE and uncover novel clinical associations in male versus female SLE patients. METHODS: We used a de-identified version of the Vanderbilt University Medical Center EHR with over 2.8 million subjects. We performed PheWAS comparing 1) SLE cases vs. age, sex, and race-matched controls and 2) male vs. female SLE cases and controlled for multiple testing using a false discovery rate (FDR) of 0.05. RESULTS: We identified 1097 SLE subjects and 5735 matched controls. Comparing SLE cases to matched controls, SLE cases were more likely to have codes for SLE disease criteria. In the male vs. female SLE case-only PheWAS adjusting for age and race, males were more likely to have atrial fibrillation (AF) OR = 4.50 (FDR p = 3.23 x 10 CONCLUSION: Using PheWAS to compare males vs. females with SLE, we uncovered a novel association of increased AF in SLE males. SLE disease status was independently associated with AF even after adjusting for age, sex, race, and CAD. These results demonstrate the utility of PheWAS as an EHR discovery tool for SLE. This article is protected by copyright. All rights reserved

Developing Electronic Health Record Algorithms That Accurately Identify Patients With Systemic Lupus Erythematosus.

OBJECTIVE: To study systemic lupus erythematosus (SLE) in the electronic health record (EHR), we must accurately identify patients with SLE. Our objective was to develop and validate novel EHR algorithms that use International Classification of Diseases, Ninth Revision (ICD-9), Clinical Modification codes, laboratory testing, and medications to identify SLE patients. METHODS: We used Vanderbilt\u27s Synthetic Derivative, a de-identified version of the EHR, with 2.5 million subjects. We selected all individuals with at least 1 SLE ICD-9 code (710.0), yielding 5,959 individuals. To create a training set, 200 subjects were randomly selected for chart review. A subject was defined as a case if diagnosed with SLE by a rheumatologist, nephrologist, or dermatologist. Positive predictive values (PPVs) and sensitivity were calculated for combinations of code counts of the SLE ICD-9 code, a positive antinuclear antibody (ANA), ever use of medications, and a keyword of lupus in the problem list. The algorithms with the highest PPV were each internally validated using a random set of 100 individuals from the remaining 5,759 subjects. RESULTS: The algorithm with the highest PPV at 95% in the training set and 91% in the validation set was 3 or more counts of the SLE ICD-9 code, ANA positive (≥1:40), and ever use of both disease-modifying antirheumatic drugs and steroids, while excluding individuals with systemic sclerosis and dermatomyositis ICD-9 codes. CONCLUSION: We developed and validated the first EHR algorithm that incorporates laboratory values and medications with the SLE ICD-9 code to identify patients with SLE accurately

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

Additional file 1: of Phenome-wide association study identifies marked increased in burden of comorbidities in African Americans with systemic lupus erythematosus

Table S1. Significant codes from the PheWAS of African Americans vs. Caucasians with SLE. Figure S1. Selected SLE disease criteria codes in the PheWAS of African Americans and Cauasians with SLE. Table S2. Selected SLE criteria codes from the PheWAS of African Americans and Caucasians with SLE. Table S3. Selected codes related to renal, cardiovascular disease, and infection from the PheWAS of African American SLE cases compared to matched African American controls. Table S4. Selected codes related to SLE criteria from the PheWAS of African American SLE cases and matched African American controls. Table S5. Selected codes from the PheWAS of Caucasian SLE cases compared to matched Caucasian controls. Table S6. Conditional logistic regression models with SLE cases and matched controls. (DOCX 134 kb