Introduction: Central centrifugal cicatricial alopecia (CCCA) is a primary scarring alopecia predominantly affecting black women. Autoimmune mechanisms, including antinuclear antibody (ANA) positivity, have been hypothesized to contribute to its pathogenesis but remain underexplored. Method: Using the TriNetX database (2004–2024), we identified black women with CCCA and controls with other primary scarring alopecias. Patients were propensity score matched by current age and age at diagnosis. We compared the prevalence of ANA positivity and autoimmune comorbidities before and after alopecia diagnosis. Statistical significance was defined as an adjusted p value <0.05. Results: Among 5,811 CCCA patients and matched controls, CCCA patients were more likely to have positive ANA (11.8% vs. 2.0%, p < 0.001) and systemic lupus erythematosus (SLE) post-diagnosis (0.9% vs. 0.3%, p = 0.007). They were less likely to have type 1 diabetes pre-diagnosis (2.9% vs. 4.8%, p = 0.007) and post-diagnosis (0.8% vs. 1.3%, p = 0.024). No significant differences were found in other autoimmune diseases. Conclusion: CCCA patients had higher prevalence of ANA positivity and SLE, supporting potential autoimmune involvement. However, screening for other autoimmune diseases in asymptomatic CCCA patients may not be necessary. Further research is needed to clarify the interplay between autoimmune and metabolic pathways in CCCA.

Journal Section:
Brief Report
Keywords:
Central centrifugal cicatricial alopecia, Scarring alopecia, Hair, Autoimmune comorbidity, Systemic lupus erythematosus

Central centrifugal cicatricial alopecia (CCCA) is a primary scarring alopecia predominantly affecting black women. Pathogenesis may be multifactorial and hypothesized to involve genetic, environmental, and autoimmune factors [1‒3]. A retrospective study reported increased prevalence of antinuclear antibody (ANA) positivity in CCCA patients, suggesting possible autoimmune mechanisms underlying CCCA [4], but this relationship is relatively unexplored. Therefore, we investigated potential autoimmune associations with CCCA using a large multicenter database.

TriNetX research network was searched from October 14, 2024 to October 16, 2024 for black women with CCCA (International Classification of Diseases [ICD]-10:L66, excluding L66.0–L66.4) and other primary scarring alopecias (controls) (ICD-10:L66.0–L66.4, excluding L66.8–L66.9) from 2004 to 2024. Discoid lupus (ICD-10:L93.0) patients were excluded. Patients were propensity score matched by current age and age at diagnosis. We analyzed autoimmune comorbidities and ANA positivity before and ≥1-day after alopecia diagnosis. Benjamini-Hochberg method was applied to correct for multiple hypothesis testing with significance defined as adjusted p value <0.05.

We analyzed 5,811 CCCA patients and 5,811 matched controls. CCCA patients versus controls were older at diagnosis (49.7 vs. 35.0 years, respectively, p < 0.001), more often had positive ANA (11.8% vs. 2.0%, respectively, p < 0.001), and less often had comorbid type 1 diabetes (T1DM) (2.9% vs. 4.8%, respectively, p = 0.007) before alopecia diagnosis (Table 1). CCCA patients versus controls were more often diagnosed with systemic lupus erythematosus (SLE) (0.9% vs. 0.3%, respectively, p = 0.007) and less often diagnosed with T1DM (0.8% vs. 1.3%, respectively, p = 0.024) after alopecia diagnosis (Table 2). There were no differences in pre- and post-diagnosis prevalences of other autoimmune diseases (all p > 0.05).

Table 1.

Demographics of black women with central centrifugal cicatricial alopecia and other primary scarring alopecias after propensity score matching

CCCA (n = 5,811)Other primary scarring alopecia (n = 5,811)p value
Current age, years±SD 53.3±14.7 49.9±18.9 <0.001 
Age at index, years±SD 48.6±14.6 45.6±18.2 <0.001 
Diagnosis, n (%) 
 Other cicatricial alopecia 2,423 (41.7%) - - 
 Cicatricial alopecia, unspecified 3,954 (68.0%) - - 
 Dissecting cellulitis - 3,442 (59.2%) - 
 Lichen planopilaris - 1,599 (27.5%) - 
 Atrophoderma vermiculatum - 635 (10.9%) - 
 Folliculitis decalvans - 128 (2.2%) - 
 Pseudopelade - 14 (0.2%) - 
Autoimmune comorbidity* 
 Type 1 diabetes mellitus 166 (2.9%) 281 (4.8%) 0.007 
 Autoimmune thyroiditis 44 (0.8%) 38 (0.7%) 0.787 
 Systemic lupus erythematosus 105 (1.8%) 80 (1.4%) 0.190 
 Vitiligo 47 (0.8%) 48 (0.8%) 0.918 
 Rheumatoid arthritis with rheumatoid factor 37 (0.6%) 40 (0.7%) 0.854 
 Other rheumatoid arthritis 144 (2.5%) 160 (2.8%) 0.616 
 Scleroderma 21 (0.4%) 20 (0.3%) 0.918 
 Sjogren’s 81 (1.4%) 62 (1.1%) 0.220 
 Myasthenia gravis 16 (0.3%) 19 (0.3%) 0.853 
 Celiac diseasea 10 (–) 12 (0.2%) - 
 Ulcerative colitis 25 (0.4%) 45 (0.8%) 0.112 
 Multiple sclerosis 46 (0.8%) 31 (0.5%) 0.201 
 Polymyalgia rheumaticaa 10 (–) 20 (0.3%) - 
Laboratory* 
 ANA-positiveb 43/364 (11.8%) 11/546 (2.0%) <0.001 
CCCA (n = 5,811)Other primary scarring alopecia (n = 5,811)p value
Current age, years±SD 53.3±14.7 49.9±18.9 <0.001 
Age at index, years±SD 48.6±14.6 45.6±18.2 <0.001 
Diagnosis, n (%) 
 Other cicatricial alopecia 2,423 (41.7%) - - 
 Cicatricial alopecia, unspecified 3,954 (68.0%) - - 
 Dissecting cellulitis - 3,442 (59.2%) - 
 Lichen planopilaris - 1,599 (27.5%) - 
 Atrophoderma vermiculatum - 635 (10.9%) - 
 Folliculitis decalvans - 128 (2.2%) - 
 Pseudopelade - 14 (0.2%) - 
Autoimmune comorbidity* 
 Type 1 diabetes mellitus 166 (2.9%) 281 (4.8%) 0.007 
 Autoimmune thyroiditis 44 (0.8%) 38 (0.7%) 0.787 
 Systemic lupus erythematosus 105 (1.8%) 80 (1.4%) 0.190 
 Vitiligo 47 (0.8%) 48 (0.8%) 0.918 
 Rheumatoid arthritis with rheumatoid factor 37 (0.6%) 40 (0.7%) 0.854 
 Other rheumatoid arthritis 144 (2.5%) 160 (2.8%) 0.616 
 Scleroderma 21 (0.4%) 20 (0.3%) 0.918 
 Sjogren’s 81 (1.4%) 62 (1.1%) 0.220 
 Myasthenia gravis 16 (0.3%) 19 (0.3%) 0.853 
 Celiac diseasea 10 (–) 12 (0.2%) - 
 Ulcerative colitis 25 (0.4%) 45 (0.8%) 0.112 
 Multiple sclerosis 46 (0.8%) 31 (0.5%) 0.201 
 Polymyalgia rheumaticaa 10 (–) 20 (0.3%) - 
Laboratory* 
 ANA-positiveb 43/364 (11.8%) 11/546 (2.0%) <0.001 

Bold values are statistically significant (p < 0.05).

ANA, antinuclear antibody; CCCA, central centrifugal cicatricial alopecia; SD, standard deviation.

*p values are Benjamini-Hochberg-adjusted.

aWhen a query returns a single count (<10), TriNetX obfuscates patient counts by reporting a count of 10, preventing analysis.

bOther primary scarring alopecia patients were more likely to have ANA testing than CCCA patients (546/5,811 [9.4%] vs. 64/5,811 [6.2%], respectively, p < 0.001).

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Table 2.

Prevalence of autoimmune comorbidities in black women after central centrifugal cicatricial alopecia and other primary scarring alopecia diagnoses

CCCAOther primary scarring alopeciaRisk difference95% CIp value
Autoimmune comorbidity*,a 
 Type 1 diabetes mellitus 0.8% (44/5,721) 1.3% (72/5,611) −0.005 −0.009, −0.001 0.024 
 Autoimmune thyroiditis 0.4% (23/5,845) 0.4% (24/5,852) −0.000 −0.002, 0.002 0.887 
 Systemic lupus erythematosus 0.9% (51/5,791) 0.3% (19/5,808) 0.006 0.003, 0.008 0.007 
 Vitiligo 0.4% (21/5,844) 0.2% (11/5,840) 0.002 −0.000, 0.004 0.135 
 Rheumatoid arthritisb 1.3% (76/5,745) 1.0% (60/5,723) 0.003 −0.001, 0.007 0.223 
 Sclerodermac −(10/5,869) −(10/5,869) - - - 
 Sjogren’s 0.8% (47/5,808) 0.5% (30/5,826) 0.003 −0.000, 0.006 0.117 
 Myasthenia gravisc 0.3% (19/5,876) −(10/5,870) - - - 
 Celiac diseasec −(10/5,883) −(10/5,878) - - - 
 Ulcerative colitis 0.2% (11/5,860) 0.3% (18/5,844) −0.001 −0.003, 0.001 0.223 
 Multiple sclerosisc 0.2% (12/5,843) −(10/5,855) - - - 
 Polymyalgia rheumaticac 0.2% (11/5,880) −(10/5,870) - - - 
Laboratorya 
 ANA-positivec 6.4% (18/282) −(10/253) - - - 
CCCAOther primary scarring alopeciaRisk difference95% CIp value
Autoimmune comorbidity*,a 
 Type 1 diabetes mellitus 0.8% (44/5,721) 1.3% (72/5,611) −0.005 −0.009, −0.001 0.024 
 Autoimmune thyroiditis 0.4% (23/5,845) 0.4% (24/5,852) −0.000 −0.002, 0.002 0.887 
 Systemic lupus erythematosus 0.9% (51/5,791) 0.3% (19/5,808) 0.006 0.003, 0.008 0.007 
 Vitiligo 0.4% (21/5,844) 0.2% (11/5,840) 0.002 −0.000, 0.004 0.135 
 Rheumatoid arthritisb 1.3% (76/5,745) 1.0% (60/5,723) 0.003 −0.001, 0.007 0.223 
 Sclerodermac −(10/5,869) −(10/5,869) - - - 
 Sjogren’s 0.8% (47/5,808) 0.5% (30/5,826) 0.003 −0.000, 0.006 0.117 
 Myasthenia gravisc 0.3% (19/5,876) −(10/5,870) - - - 
 Celiac diseasec −(10/5,883) −(10/5,878) - - - 
 Ulcerative colitis 0.2% (11/5,860) 0.3% (18/5,844) −0.001 −0.003, 0.001 0.223 
 Multiple sclerosisc 0.2% (12/5,843) −(10/5,855) - - - 
 Polymyalgia rheumaticac 0.2% (11/5,880) −(10/5,870) - - - 
Laboratorya 
 ANA-positivec 6.4% (18/282) −(10/253) - - - 

Bold values are statistically significant (p < 0.05).

ANA, antinuclear antibody; CCCA, central centrifugal cicatricial alopecia; CI, confidence interval.

*p values are Benjamini-Hochberg-adjusted.

aAny patient whose medical event happened outside the designated study window was excluded from analysis, resulting in different cohort sizes for each analysis.

bRheumatoid arthritis with rheumatoid factor and other rheumatoid arthritis.

cWhen a query returns a single count (<10), TriNetX obfuscates patient counts by reporting a count of 10, preventing analysis.

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We found that CCCA patients versus controls were more likely to have positive ANA and higher risk of SLE, with no difference in risk of most other autoimmune disorders. Similarly, a retrospective study of 79 CCCA patients found higher prevalence of positive ANA in CCCA patients versus non-scarring alopecia controls (36.7% vs. 16.0%, respectively, p = 0.033) [4]. Another retrospective study of 153 CCCA women found no difference in the overall prevalence of autoimmune disorders between CCCA patients and non-scarring alopecia controls (22.9% vs. 16.3%, respectively, p = 0.195) [5] but did not analyze specific autoimmune disorders individually. A retrospective study of 53 CCCA patients reported 2% prevalence of SLE and 2% prevalence of vitiligo but lacked autoimmune data for their control group to assess for statistical significance [6].

We also found decreased prevalence and risk of T1DM in CCCA patients versus controls. While previous studies have not explored associations between T1DM and CCCA, several have reported an association with type 2 diabetes [1, 2, 4, 7, 8]. In a retrospective study of 395 women with CCCA and 39,280 controls without CCCA, type 1 diabetes prevalence was 37% and 12%, respectively (p < 0.05) [8]. Therefore, diabetes in CCCA patients may be primarily mediated by metabolic, rather than autoimmune pathways. A proteomic study identified downregulation of several metabolic proteins in CCCA-affected scalps, suggesting a link between metabolic dysregulation and CCCA [9]. Combined with our findings, complex interactions between metabolic and autoimmune pathways may underlie the pathogenesis of CCCA, warranting further investigation.

Limitations include retrospective database design, potential miscoding, and unknown ANA titers. There were no CCCA-specific ICD-10 codes at the time this study took place, and the database does not have information on histopathological confirmation of CCCA cases. Furthermore, using a database limits the ability to review individual charts to confirm diagnoses. The reliance on diagnosis codes may lead to inaccurate sample selection and limit the reliability of prevalence estimates. Future prospective studies with CCCA histopathological confirmation are necessary to confirm these findings.

In conclusion, our findings suggest that CCCA may be associated with higher prevalence of ANA positivity and SLE compared to other primary scarring alopecias. However, CCCA patients did not have an increased pre- and post-diagnosis prevalence of most autoimmune disorders. Therefore, dermatologists may consider baseline ANA screening in CCCA patients, and subsequent ANA testing if review of systems suggest concern for SLE. Based on our study, screening for other autoimmune disorders in absence of symptoms is not warranted.

This retrospective review of patient data is exempt from informed consent and did not require ethical approval in accordance with local/national guidelines. The data reviewed is a secondary analysis of existing data, does not involve intervention or interaction with human subjects, and is de-identified per the de-identification standard defined in Section §164.514(a) of the HIPAA Privacy Rule. The process by which the data are de-identified is attested to through a formal determination by a qualified expert as defined in Section §164.514(b)(1) of the HIPAA Privacy Rule. This formal determination by a qualified expert refreshed on December 2020.

The authors have no conflicts of interest to declare.

This study was not supported by any sponsor or funder.

Conceptualization: M.M.O. and S.R.L.; methodology, M.M.O., A.S., and S.R.L.; data curation and formal analysis: A.S.; investigation: M.M.O. and A.S.; supervision: S.R.L.; writing – original draft: M.M.O.; and writing – review and editing: A.S. and S.R.L.

Additional Information

Michael M. Ong and Amit Singal contributed equally to this work.

The data that support the findings of this study are not publicly available due to the inclusion of protected health information and restrictions imposed by the data provider, TriNetX, which prohibit public sharing of raw data. However, aggregate-level data or analyses supporting findings of this study are available from the corresponding author (S.R.L.) upon reasonable request and with permission from TriNetX.

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