Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Jul 1.
Published in final edited form as: J Am Acad Dermatol. 2021 Jul 29;87(1):197–199. doi: 10.1016/j.jaad.2021.07.033

Comorbidities Associated with Granuloma Annulare: A Case-Control Study in the All of Us Research Program

Audrey C Leasure 1, William Damsky 2,3, Jeffrey M Cohen 2
PMCID: PMC8799765  NIHMSID: NIHMS1729814  PMID: 34333076

To the Editor:

Granuloma annulare (GA) is an inflammatory skin disorder with an incompletely understood pathogenesis. Prior single-center studies have suggested associations of GA with diabetes, hyperlipidemia, and thyroid disease, but these associations have been inconsistently reported and have not been validated in multi-center studies.1-3 Here, we aim to evaluate associations between GA and several comorbidities in the All of Us Research Program, a National Institutes of Health database that is designed to provide health and genetic data on over 1 million Americans focusing on groups that have generally been underrepresented in research.4

We performed a nested, matched case-control analysis in the All of Us cohort, which includes adults age 18 and older from 2018 to present. Data are available at www.allofus.nih.gov. GA cases were identified in electronic health record data using ICD-10-CM code L92.0 and/or SNOMED Code 65508009. We used nearest-neighbor propensity score matching to select 4 age, sex, and race matched controls for each GA case. We compared comorbidities between cases and controls using Pearson’s Chi-squared test or Fisher exact test for categorical variables and the unpaired t-test for continuous variables. We used logistics regression to determine whether comorbidities were associated with GA in multivariable analyses. Multivariable models were built by inclusion of universal confounders (age, sex), a priori associations, and covariates with significance of p<0.1 in univariable analysis, followed by backwards elimination of covariates with significance of p>0.1 or with evidence of collinearity.

Of the 203,813 All of Us participants with available electronic health record data, we identified 177 GA cases with complete data (average age 61 years [SD 15], 80% female) and 708 matched controls. Age, sex, and race/ethnicity were well matched between cases and controls (all p>0.9). Compared to controls, GA cases were more likely to have ever smoked (50% vs 38%, p=0.007), to have hyperlipidemia (62% vs 50%, p=0.006), type II diabetes (24% vs 16%, p=0.03), ischemic heart disease (12% vs 6%, p=0.02), hypothyroidism (29% vs 17%, p<0.001), and autoimmune disease (16% vs 10%, p=0.03) (Table 1). In multivariable analysis, ever smoker, hyperlipidemia, and hypothyroidism remained significantly associated with GA (Table 2).

Table 1.

Clinical Characteristics of GA Cases versus Age, Sex, and Race Matched Controls in All of Us

Matched Controls GA p
n 708 177
Age (mean (SD)) 60.6 (15.0) 60.6 (15.1) 1.00
Female (%) 564 (79.7) 142 (79.7) 1.00
Race/ethnicity (%) 1.00
Asian 12 (1.7) 3 (1.7)
Black 40 (5.6) 10 (5.6)
Hispanic 36 (5.1) 9 (5.1)
Other 28 (4.0) 7 (4.0)
White 592 (83.6) 148 (83.6)
Ever smoker (%) 266 (38.2) 87 (49.7) 0.007
Sleep apnea (%) 55 (7.8) 18 (10.2) 0.37
Hypertension (%) 346 (48.9) 98 (55.4) 0.14
Hyperlipidemia (%) 356 (50.3) 110 (62.1) 0.006
Type II DM (%) 116 (16.4) 42 (23.7) 0.03
Atrial fibrillation (%) 51 (7.2) 19 (10.7) 0.16
Ischemic heart disease (%) 45 (6.4) 21 (11.9) 0.02
Stroke (%) 27 (3.8) 6 (3.4) 0.97
Cardiovascular disease (%) 67 (9.5) 24 (13.6) 0.14
Thyroiditis (%) 21 (3.0) 6 (3.4) 0.96
Hypothyroidism (%) 121 (17.1) 52 (29.4) <0.001
Hyperthyroidism (%) 26 (3.7) 14 (7.9) 0.03
Autoimmune Disease* (%) 69 (9.7) 28 (15.8) 0.03
HIV (%) 3 (0.4) 1 (0.6) 1.00
*

Autoimmune disease includes systemic lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, thyroiditis, vitiligo, and alopecia areata.

Abbreviations: GA = granuloma annulare; SD = standard deviation; DM = diabetes mellitus; HIV = human immunodeficiency virus

Table 2.

Univariable and Multivariable Association of Comorbidities with GA

Covariate Univariable OR (95% CI) p Multivariable OR (95%CI) p
Age 1.00 (0.99-1.01) 1.00 0.98 (0.97-1.00) 0.01
Female sex 1.00 (0.66-1.49) 1.00 1.03 (0.66-1.58) 0.91
Ever smoker 1.60 (1.14-2.23) 0.006 1.54 (1.09-2.18) 0.02
Hyperlipidemia 1.62 (1.16-2.28) 0.005 1.63 (1.07-2.49) 0.02
Hypothyroidism 2.02 (1.38-2.93) <0.001 1.86 (1.23-2.80) 0.003
Type II DM 1.59 (1.06-2.35) 0.02 1.30 (0.84-2.02) 0.27
Autoimmune Disease * 1.74 (1.07-2.77) 0.02 1.47 (0.88-2.42) 0.13
*

Autoimmune disease includes systemic lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, thyroiditis, vitiligo, and alopecia areata.

Abbreviations: GA = granuloma annulare; OR = odds ratio; CI = confidence interval; DM = diabetes mellitus

Our findings extend the results of prior studies that demonstrated an association with dyslipidemia2,3 and thyroid disease.2 We found that individuals with GA had a 63% and 86% increase in the odds of having hyperlipidemia and hypothyroidism, respectively. There have been several studies both supporting and refuting an association GA with diabetes.1,5 While we observed a higher prevalence of diabetes in GA cases compared to controls, this association was not significant in multivariable analysis. Finally, we report a novel association of GA with smoking; having ever smoked was associated with a 54% increase in the odds of having GA.

While our study includes a large, diverse cohort, it is limited by ascertainment of GA using electronic health records and a lack of data on clinical features of GA. Further studies are needed to determine whether the identified associations are causally related to the pathogenesis of GA.

Funding sources:

This article has no funding source. W.D. is supported by a Career Development Award from the Dermatology Foundation.

Abbreviations

GA

granuloma annulare

CI

confidence interval

SD

standard deviation

Footnotes

Publisher's Disclaimer: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Conflicts of Interest: WD serves as a consultant for Pfizer, Eli Lilly, and TWi Biotechnology, has research funding from Pfizer, and receives licensing fees from EMD/Millipore/Sigma.

IRB Information: This study has been deemed not to be human subjects research by the Yale University Institutional Review Board (Protocol ID: 2000030328).

References

  • 1.Piette EW, Rosenbach M. Granuloma annulare: Pathogenesis, disease associations and triggers, and therapeutic options. J Am Acad Dermatol. 2016;75(3):467–479. doi: 10.1016/j.jaad.2015.03.055 [DOI] [PubMed] [Google Scholar]
  • 2.Rubin CB, Rosenbach M. Granuloma annulare: a retrospective series of 133 patients. Cutis. 2019; 103(2):102–106. [PubMed] [Google Scholar]
  • 3.Wu W, Robinson-Bostom L, Kokkotou E, Jung H-Y, Kroumpouzos G. Dyslipidemia in granuloma annulare: a case-control study. Arch Dermatol. 2012;148(10):1131–1136. doi: 10.1001/archdermatol.2012.1381 [DOI] [PubMed] [Google Scholar]
  • 4.All of Us Research Program Investigators, Denny JC, Rutter JL, et al. The “All of Us” Research Program. N Engl J Med. 2019;381(7):668–676. doi: 10.1056/NEJMsr1809937 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Veraldi S, Bencini PL, Drudi E, Caputo R. Laboratory abnormalities in granuloma annulare: a casecontrol study. British Journal of Dermatology. 1997;136(4):652–653. doi: 10.1111/j.1365-2133.1997.tb02180.x [DOI] [PubMed] [Google Scholar]

RESOURCES