Skip to main content
Top

10-04-2018 | Systemic lupus erythematosus | Article

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

Journal: Arthritis Research & Therapy

Authors: April Barnado, Robert J. Carroll, Carolyn Casey, Lee Wheless, Joshua C. Denny, Leslie J. Crofford

Publisher: BioMed Central

Abstract

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.
Literature
1.
Sundquist J, Johansson SE. The influence of socioeconomic status, ethnicity and lifestyle on body mass index in a longitudinal study. Int J Epidemiol. 1998;27:57–63.CrossRefPubMed
2.
Demas KL, Costenbader KH. Disparities in lupus care and outcomes. Curr Opin Rheumatol. 2009;21:102–9.CrossRefPubMedPubMedCentral
3.
Lim SS, Bayakly AR, Helmick CG, Gordon C, Easley KA, Drenkard C. The incidence and prevalence of systemic lupus erythematosus, 2002–2004: the Georgia Lupus Registry. Arthritis Rheum. 2014;66:357–68.CrossRef
4.
Somers EC, Marder W, Cagnoli P, Lewis EE, DeGuire P, Gordon C, et al. Population-based incidence and prevalence of systemic lupus erythematosus: the Michigan Lupus Epidemiology and Surveillance program. Arthritis Rheum. 2014;66:369–78.CrossRef
5.
Centers for Disease C, Prevention. Trends in deaths from systemic lupus erythematosus–United States, 1979–1998. MMWR Morb Mortal Wkly Rep. 2002;51:371–4.
6.
Krishnan E, Hubert HB. Ethnicity and mortality from systemic lupus erythematosus in the US. Ann Rheum Dis. 2006;65:1500–5.CrossRefPubMedPubMedCentral
7.
Pathak J, Kho AN, Denny JC. Electronic health records-driven phenotyping: challenges, recent advances, and perspectives. J Am Med Inform Assoc. 2013;20:e206–11.CrossRefPubMedPubMedCentral
8.
Ritchie MD, Denny JC, Crawford DC, Ramirez AH, Weiner JB, Pulley JM, et al. Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record. Am J Hum Genet. 2010;86:560–72.CrossRefPubMedPubMedCentral
9.
Bowton E, Field JR, Wang S, Schildcrout JS, Van Driest SL, Delaney JT, et al. Biobanks and electronic medical records: enabling cost-effective research. Sci Transl Med. 2014;6:234cm3.CrossRefPubMedPubMedCentral
10.
Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K, et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics. 2010;26:1205–10.CrossRefPubMedPubMedCentral
11.
Denny JC, Bastarache L, Ritchie MD, Carroll RJ, Zink R, Mosley JD, et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat Biotechnol. 2013;31:1102–10.CrossRefPubMedPubMedCentral
12.
Denny JC, Crawford DC, Ritchie MD, Bielinski SJ, Basford MA, Bradford Y, et al. Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies. Am J Hum Genet. 2011;89:529–42.CrossRefPubMedPubMedCentral
13.
Hebbring SJ, Schrodi SJ, Ye Z, Zhou Z, Page D, Brilliant MH. A PheWAS approach in studying HLA-DRB1*1501. Genes Immun. 2013;14:187–91.CrossRefPubMedPubMedCentral
14.
Liao KP, Kurreeman F, Li G, Duclos G, Murphy S, Guzman R, et al. Associations of autoantibodies, autoimmune risk alleles, and clinical diagnoses from the electronic medical records in rheumatoid arthritis cases and non-rheumatoid arthritis controls. Arthritis Rheum. 2013;65:571–81.CrossRefPubMedPubMedCentral
15.
Doss J, Mo H, Carroll RJ, Crofford LJ, Denny JC. Phenome-wide association study of rheumatoid arthritis subgroups identifies association between seronegative disease and fibromyalgia. Arthritis Rheum. 2017;69:291–300.CrossRef
16.
Liao KP, Sparks JA, Hejblum BP, Kuo IH, Cui J, Lahey LJ, et al. Phenome-wide association study of autoantibodies to citrullinated and non-citrullinated epitopes in rheumatoid arthritis. Arthritis Rheum. 2017;69:742–9.CrossRef
17.
Denny JC, Bastarache L, Roden DM. Phenome-wide association studies as a tool to advance precision medicine. Annu Rev Genomics Hum Genet. 2016;17:353–73.CrossRefPubMedPubMedCentral
18.
Bush WS, Oetjens MT, Crawford DC. Unravelling the human genome-phenome relationship using phenome-wide association studies. Nat Rev Genet. 2016;17:129–45.CrossRefPubMed
19.
Roden DM, Pulley JM, Basford MA, Bernard GR, Clayton EW, Balser JR, et al. Development of a large-scale de-identified DNA biobank to enable personalized medicine. Clin Pharmacol Ther. 2008;84:362–9.CrossRefPubMedPubMedCentral
20.
Barnado A, Casey C, Carroll RJ, Wheless L, Denny JC, Crofford LJ. Developing electronic health record algorithms that accurately identify patients with systemic lupus erythematosus. Arthritis Care Res. 2017;69:687–93.CrossRef
21.
Schildcrout JS, Denny JC, Bowton E, Gregg W, Pulley JM, Basford MA, et al. Optimizing drug outcomes through pharmacogenetics: a case for preemptive genotyping. Clin Pharmacol Ther. 2012;92:235–42.CrossRefPubMedPubMedCentral
22.
Dumitrescu L, Ritchie MD, Brown-Gentry K, Pulley JM, Basford M, Denny JC, et al. Assessing the accuracy of observer-reported ancestry in a biorepository linked to electronic medical records. Genet Med. 2010;12:648–50.CrossRefPubMedPubMedCentral
23.
Carroll RJ, Bastarache L, Denny JC. R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment. Bioinformatics. 2014;30:2375–6.CrossRefPubMedPubMedCentral
24.
Hochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum. 1997;40:1725.CrossRefPubMed
25.
Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Heart disease and stroke statistics-2016 update: a report from the American Heart Association. Circulation. 2016;133:e38–360.CrossRefPubMed
26.
Feldman CH, Hiraki LT, Winkelmayer WC, Marty FM, Franklin JM, Kim SC, et al. Serious infections among adult Medicaid beneficiaries with systemic lupus erythematosus and lupus nephritis. Arthritis Rheum. 2015;67:1577–85.CrossRef
27.
Hiraki LT, Feldman CH, Marty FM, Winkelmayer WC, Guan H, Costenbader KH. Serious infection rates among children with systemic lupus erythematosus enrolled in Medicaid. Arthritis Care Res. 2017;69:1620–6.CrossRef
28.
Gonzalez LA, Toloza SM, McGwin G Jr, Alarcon GS. Ethnicity in systemic lupus erythematosus (SLE): its influence on susceptibility and outcomes. Lupus. 2013;22:1214–24.CrossRefPubMed
29.
Fernandez M, Alarcon GS, Calvo-Alen J, Andrade R, McGwin G Jr, Vila LM, et al. A multiethnic, multicenter cohort of patients with systemic lupus erythematosus (SLE) as a model for the study of ethnic disparities in SLE. Arthritis Rheum. 2007;57:576–84.CrossRefPubMed
30.
Alarcon GS, McGwin G Jr, Petri M, Ramsey-Goldman R, Fessler BJ, Vila LM, et al. Time to renal disease and end-stage renal disease in PROFILE: a multiethnic lupus cohort. PLoS Med. 2006;e396:3.
31.
Burgos PI, McGwin G Jr, Pons-Estel GJ, Reveille JD, Alarcon GS, Vila LM. US patients of Hispanic and African ancestry develop lupus nephritis early in the disease course: data from LUMINA, a multiethnic US cohort (LUMINA LXXIV). Ann Rheum Dis. 2011;70:393–4.CrossRefPubMed
32.
Korbet SM, Schwartz MM, Evans J, Lewis EJ, Collaborative Study G. Severe lupus nephritis: racial differences in presentation and outcome. J Am Soc Nephrol. 2007;18:244–54.CrossRefPubMed
33.
Hiraki LT, Lu B, Alexander SR, Shaykevich T, Alarcon GS, Solomon DH, et al. End-stage renal disease due to lupus nephritis among children in the US, 1995–2006. Arthritis Rheum. 2011;63:1988–97.CrossRefPubMedPubMedCentral
34.
Shaharir SS, Mustafar R, Mohd R, Mohd Said MS, Gafor HA. Persistent hypertension in lupus nephritis and the associated risk factors. Clin Rheumatol. 2015;34:93–7.CrossRefPubMed
35.
Scalzi LV, Hollenbeak CS, Wang L. Racial disparities in age at time of cardiovascular events and cardiovascular-related death in patients with systemic lupus erythematosus. Arthritis Rheum. 2010;62:2767–75.CrossRefPubMedPubMedCentral
36.
Gomez-Puerta JA, Feldman CH, Alarcon GS, Guan H, Winkelmayer WC, Costenbader KH. Racial and ethnic differences in mortality and cardiovascular events among patients with end-stage renal disease due to lupus nephritis. Arthritis Care Res. 2015;67:1453–62.CrossRef
37.
Maynard JW, Fang H, Petri M. Low socioeconomic status is associated with cardiovascular risk factors and outcomes in systemic lupus erythematosus. J Rheumatol. 2012;39:777–83.CrossRefPubMedPubMedCentral
38.
Petri M, Perez-Gutthann S, Spence D, Hochberg MC. Risk factors for coronary artery disease in patients with systemic lupus erythematosus. Am J Med. 1992;93:513–9.CrossRefPubMed
39.
Toloza SM, Uribe AG, McGwin G Jr, Alarcon GS, Fessler BJ, Bastian HM, et al. Systemic lupus erythematosus in a multiethnic US cohort (LUMINA). XXIII. Baseline predictors of vascular events. Arthritis Rheum. 2004;50:3947–57.CrossRefPubMed
40.
Schoenfeld SR, Kasturi S, Costenbader KH. The epidemiology of atherosclerotic cardiovascular disease among patients with SLE: a systematic review. Semin Arthritis Rheum. 2013;43:77–95.CrossRefPubMed
41.
Hak AE, Karlson EW, Feskanich D, Stampfer MJ, Costenbader KH. Systemic lupus erythematosus and the risk of cardiovascular disease: results from the nurses’ health study. Arthritis Rheum. 2009;61:1396–402.CrossRefPubMedPubMedCentral
42.
Ward MM. Premature morbidity from cardiovascular and cerebrovascular diseases in women with systemic lupus erythematosus. Arthritis Rheum. 1999;42:338–46.CrossRefPubMed
43.
Urowitz MB, Gladman D, Ibanez D, Bae SC, Sanchez-Guerrero J, Gordon C, et al. Atherosclerotic vascular events in a multinational inception cohort of systemic lupus erythematosus. Arthritis Care Res. 2010;62:881–7.CrossRef
44.
Burgos PI, Vila LM, Reveille JD, Alarcon GS. Peripheral vascular damage in systemic lupus erythematosus: data from LUMINA, a large multi-ethnic U.S. cohort (LXIX). Lupus. 2009;18:1303–8.CrossRefPubMedPubMedCentral
45.
Tan TC, Fang H, Magder LS, Petri MA. Differences between male and female systemic lupus erythematosus in a multiethnic population. J Rheumatol. 2012;39:759–69.CrossRefPubMedPubMedCentral
46.
Gladman DD, Hussain F, Ibanez D, Urowitz MB. The nature and outcome of infection in systemic lupus erythematosus. Lupus. 2002;11:234–9.CrossRefPubMed
47.
Ginzler E, Diamond H, Kaplan D, Weiner M, Schlesinger M, Seleznick M. Computer analysis of factors influencing frequency of infection in systemic lupus erythematosus. Arthritis Rheum. 1978;21:37–44.CrossRefPubMed
48.
Bosch X, Guilabert A, Pallares L, Cerveral R, Ramos-Casals M, Bove A, et al. Infections in systemic lupus erythematosus: a prospective and controlled study of 110 patients. Lupus. 2006;15:584–9.CrossRefPubMed
49.
Bombardier C, Gladman DD, Urowitz MB, Caron D, Chang CH. Derivation of the SLEDAI. A disease activity index for lupus patients. The Committee on Prognosis Studies in SLE. Arthritis Rheum. 1992;35:630–40.CrossRefPubMed
50.
Gladman D, Ginzler E, Goldsmith C, Fortin P, Liang M, Urowitz M, et al. The development and initial validation of the Systemic Lupus International Collaborating Clinics/American College of Rheumatology damage index for systemic lupus erythematosus. Arthritis Rheum. 1996;39:363–9.CrossRefPubMed
51.
Ananthakrishnan AN, Cagan A, Cai T, Gainer VS, Shaw SY, Savova G, et al. Identification of nonresponse to treatment using narrative data in an electronic health record inflammatory bowel disease cohort. Inflamm Bowel Dis. 2016;22:151–8.CrossRefPubMedPubMedCentral
52.
Liao KP, Ananthakrishnan AN, Kumar V, Xia Z, Cagan A, Gainer VS, et al. Methods to develop an electronic medical record phenotype algorithm to copare the risk of coronary artery disease across 3 chronic disease cohorts. PLoS One. 2015;10:8.