Background
Health disparities are defined as “differences in the incidence, prevalence, mortality and burden of diseases and other adverse health conditions that exist among specific population groups in the US” [
1]. Among rheumatic diseases, systemic lupus erythematosus (SLE) has one of the highest mortality rates and highest rates of health disparity [
2]. SLE disproportionately affects African Americans, particularly female African Americans, who have nearly threefold higher incidence of SLE compared to Caucasians [
3]. Female African Americans also have a younger age of onset and increased rates of renal disease compared to Caucasians [
3,
4]. Female African Americans in the USA have the highest SLE mortality rates [
5,
6]. Studies, however, have not fully examined differences in comorbidities in African Americans compared to Caucasians with SLE.
Racial disparities in SLE have mainly been studied using cohort and administrative database studies. Cohort studies typically have focused on SLE-related disease measures such as disease activity and may not capture other important comorbidities. Alternatively, administrative studies may not capture detailed data on a patient’s SLE disease course or comorbidities. Therefore, studies have not fully examined the impact of both the SLE disease course and comorbidities on outcomes. Electronic health records (EHRs) serve as an efficient and cost-effective discovery tool [
7‐
9] to provide detailed data on both a patient’s SLE disease course and comorbidities. One method to harness the power of the longitudinal, clinical data in the EHR is the phenome-wide association study (PheWAS). Similar to the way a genome-wide association study (GWAS) scans across the genome, a PheWAS scans across diseases in the EHR, using aggregations of billing codes. PheWAS have uncovered novel genetic associations in multiple autoimmune diseases [
10‐
13] and have found novel phenotypes with autoantibodies in rheumatoid arthritis [
14‐
16]. PheWAS has also been validated across multiple EHRs and using orthogonal methods [
11‐
13,
17,
18]. To the best of our knowledge, PheWAS have not been used in SLE to examine differences in comorbidities between African Americans and Caucasians with SLE. We hypothesized that PheWAS could take advantage of the longitudinal data in the EHR to systematically test for differences in comorbidities that would inform racial disparities in SLE.
Discussion
Using PheWAS in a large cohort of 1097 subjects with SLE using EHR data with decades of follow up, we uncovered an increased burden of comorbidities across all organ systems among African Americans compared to Caucasians with SLE. African Americans with SLE were two to four times more likely to have renal disease, cardiovascular disease, and infections. To the best of our knowledge, this is the first study to use PheWAS to examine racial disparities between African Americans and Caucasians with SLE. Since some comorbidities are more frequent in non-SLE African Americans compared with Caucasians [
25], we determined the impact of SLE on comorbidities in African Americans. Compared to matched African American controls, African American subjects with SLE were significantly more likely to have comorbidities in all organ systems, notably in renal, cardiovascular, and infectious diseases.
PheWAS enables a systematic assessment of diverse phenotypes in the EHR, building upon both traditional cohort and administrative database studies. PheWAS has the potential to capture both SLE disease-related data such as ACR SLE criteria [
24], as well as other comorbidities. Data on these comorbidities may not be collected in traditional cohort studies, while administrative database studies may not adequately capture SLE-related data. Further, administrative databases can have a fairly short duration of follow up [
26,
27]. In contrast, our EHR has follow up over several decades with subjects with SLE having on average 9 years of follow up [
20]. PheWAS has the power to capture diverse comorbidities in the EHR and uncover how these comorbidities contribute to racial disparities in SLE.
Compared to Caucasians, African American patients with SLE have increased renal disease. These disparities have been attributed to both genetic and non-genetic factors such as the environment and socioeconomic status [
28]. As expected, we observed an increased burden of renal disease in African Americans compared to Caucasians with SLE, which agrees with findings in prior SLE cohorts [
29‐
34]. While PheWAS confirmed known renal disparities in African Americans with SLE, it also uncovered an increased cardiovascular disease burden, which has not been previously well-described. African Americans with SLE were three times more likely to have CAD compared to Caucasians with SLE. Administrative studies have shown increased CAD in African Americans compared to Caucasians with SLE when restricting analyses to inpatient encounters and subsets of patients with SLE [
35,
36]. Our study builds upon these studies by including all patients with SLE and capturing CAD in both inpatient and outpatient encounters. In contrast to these administrative database studies, two cohort studies did not find increased CAD in African Americans compared to Caucasians with SLE [
37‐
39]. These differences could be due to different SLE patient populations. In contrast to traditional SLE cohorts, our EHR SLE cohort may represent a more community-based group of patients with SLE. Further, unless a cohort study collects data on a specific outcome, these outcomes may be underreported, as they may rely on either patient report or traditional methods that often focus on disease activity measures. These SLE cohorts also had a low frequency of CAD, myocardial infarction, and CVD events, with one study having only 34 patients with any vascular event [
39]. These low-frequency events may have made these studies underpowered to detect differences in CAD in African Americans compared to Caucasians with SLE. In our EHR cohort, looking across multiple codes that captured CAD, we had 177 events.
In addition to CAD, African Americans with SLE were three times more likely to have CHF and CVD and more than four times more likely to have hypertension compared to Caucasians. There are fewer studies comparing risk of these cardiovascular diseases in African Americans to Caucasians with SLE, with mixed results [
36,
37]. Specifically, in one cohort, there were no differences in rates of CVD and PVD comparing African Americans to Caucasians [
39]. This study included only 18 subjects with CVD and 5 with PVD in contrast to approximately 223 subjects with CVD and 25 with PVD in our study [
39].
Beyond the increased renal and cardiac disease burden, African Americans with SLE had an increase in infectious diseases compared to Caucasians with SLE. African Americans were more than 3.5 times more likely to have pneumonia and twice as likely to have bacteremia and sepsis. Our study agrees with two studies using the Medicaid administrative database that identified an increased risk of serious infections in African Americans compared to Caucasians with SLE, with the most common being bacteremia, pneumonia, and cellulitis [
26,
27]. Our study builds upon these studies by including both inpatient and outpatient infections and offering a longer follow up of 9 years compared to the mean follow up of the studies of 2.5 years.
To account for racial differences in comorbidities, we compared African Americans with SLE to matched African American controls, particularly since many of these comorbidities are more common in African Americans. As expected, African Americans with SLE had more codes related to ACR SLE criteria [
24] showing that PheWAS can identify SLE disease characteristics in the EHR. Compared to matched controls, African Americans with SLE also had more comorbidities across all organ systems. Notably, African Americans with SLE were more likely to have codes for chronic kidney disease (CKD), end-stage renal disease (ESRD), and renal transplant. Using a conditional logistic regression model with SLE cases and matched controls (including both Caucasians and African Americans), adjusting for age, sex, and race, SLE remained independently associated with CKD, ESRD, and renal transplant suggesting that African American race was not the sole driver for increased renal disease.
Compared to matched controls, African Americans with SLE also had more codes for CAD, CVD, PVD, and arrhythmias. While a twofold to threefold increase in CAD has been described in subjects with SLE compared to population controls [
40], there are few data comparing CAD events in African Americans with SLE compared to matched controls. One of the largest US population-based studies, the Nurses’ Health study, compared rates of CAD in participants with and without SLE showing a twofold to threefold increase in CAD events [
41]. Notably, the cohort was all female and 95% Caucasian [
41]. Our study is unique in that it included both male and female SLE patients and focused on African Americans. For other cardiac comorbidities, there are few studies comparing African American patients with SLE to matched controls [
41,
42]. Further, studies often restrict analyses to subsets of patients with SLE [
41,
42] while no studies directly compare patients with SLE to controls for PVD [
43,
44] and AF. Our study builds upon large population-based studies by including male subjects and African Americans with SLE, who are often understudied and have adverse outcomes [
45]. Our study also demonstrates novel findings of increased PVD and AF in African American patients with SLE compared to controls.
African Americans with SLE also had increased risk of multiple infections compared to matched controls. This increased risk of infection in SLE is likely due to immunosuppressant medications, the disease itself, or an interaction between these factors [
46‐
48]. Two recent studies using the US Medicaid database investigated infection rates among different SLE patients but did not compare patients with SLE to matched controls [
26,
27]. Our study establishes an increased risk of infection in African Americans with SLE compared to matched controls.
Our EHR-based PheWAS study has limitations. We used a previously validated algorithm to identify patients with SLE with a positive predictive value (PPV) of 89% and sensitivity of 86% [
20]. Despite this algorithm’s strong test characteristics, we may have captured some subjects who do not have a SLE diagnosis. Our clinical EHR data, in contrast to prospective cohort studies, does not contain disease activity and damage measures such as the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) [
49] and Systemic Lupus International Collaborating Clinics Damage Index (SDI) [
50], as these measures are not collected routinely in clinical practice. Thus, we cannot adjust for disease activity or damage in PheWAS. EHR-based algorithms that assess treatment response in inflammatory bowel disease [
51] and CAD risk in inflammatory bowel disease and RA [
52] have been created. Currently, however, there are no published, EHR-based algorithms assessing disease severity and activity in autoimmune diseases. Future directions include developing these algorithms in SLE. Next, this PheWAS was performed using billing codes at Vanderbilt only. Patients can receive care in multiple healthcare systems, which may not be documented in Vanderbilt’s EHR. These potential missed diagnoses, however, would bias us to the null result. Missing data could be non-randomly distribute, with more occurring in the controls in whom EHR follow up was shorter compared to patients with SLE. We adjusted for EHR follow-up time, which did not alter our main findings. Last, our study was performed using a single institution’s EHR, potentially limiting generalizability of our results to other patients with SLE. Using an EHR-based cohort to study SLE, however, may capture a wider net of patients with SLE that are more representative of the community compared to patients with SLE recruited into a cohort. We did not have sufficient numbers of Hispanics or Asians, reflecting the demographics of middle Tennessee, to study patients with SLE with these ethnicities in our PheWAS. However, our EHR cohort included male subjects and African Americans with SLE, who are often understudied [
45]. We acknowledge that the African American population in the USA is admixed, and these findings associated with the race construct could represent cultural and socioeconomic factors as well as genetic ancestry. Unfortunately, our de-identified resource does not contain socioeconomic data such as income level or insurance coverage, so we are unable to adjust for these factors in our PheWAS.