December 8, 2025Open Access

Cutaneous Opportunistic Mycobacterial and Fungal Infections in Adult-Onset Immunodeficiency Due to Anti-Interferon-Gamma Autoantibodies – Decoding Skin Involvement Patterns

Key Points

Cutaneous infections show high predictive capability for differentiating between mycobacterial and fungal infections in immunocompromised individuals.
Among 61 patients with adult-onset immunodeficiency, 70 infectious episodes were analyzed, 50 of which were mycobacterial.
The model's area under the ROC curve was 0.94, indicating excellent accuracy in distinguishing cutaneous infection types.
Clinical clues such as neck lesions and lymphadenopathy may guide timely empirical therapy in cases pending confirmation.

Abstract

Abstract Background Adult-onset immunodeficiency (AOID) due to anti-interferon-gamma autoantibodies (AIGA) predisposes patients to multiple opportunistic infections (OIs), including cutaneous involvement. However, data specifically addressing cutaneous OIs in AOID remain limited. This study aimed to characterize and compare clinical and laboratory features, with a focus on cutaneous OIs caused by mycobacteria and fungi. Methods A retrospective chart review was conducted on AOID patients with cutaneous OIs in Chiang Mai and Khon Kaen University Hospital from January 2000 to December 2020. Cases with infection due to Mycobacterium species—both Mycobacterium tuberculosis complex (MTB) and non-tuberculous mycobacteria (NTM)—and fungal pathogens were included. Clinical characteristics and laboratory parameters were analyzed, and a multivariate predictive model was developed to differentiate between cutaneous mycobacterial and fungal infections. Results A total of 61 AOID patients with 70 cutaneous infectious episodes were identified. Among these, fifty episodes were due to Mycobacterium infection. Lesions involving the neck with concurrent lymphadenopathy were more suggestive of Mycobacterium infection. In contrast, fungal infections were associated with generalized or truncal involvement, anemia, neutrophilia, lower monocyte percentage, hyperglobulinemia, and higher levels of aspartate aminotransferase. A multivariate model incorporating these variables achieved excellent discriminatory performance (area under the receiver operating characteristic curve (AuROC): 0.94; 95% confidence interval: 0.87–0.99). Conclusions Cutaneous lesions involving the neck area and lymphadenopathy are clinical clues that suggest cutaneous Mycobacterium OIs. Nevertheless, integration of clinical features with laboratory findings enables the development of a predictive model that can effectively differentiate between cutaneous mycobacterial and fungal infections. This predictive model may aid in selecting appropriate empirical antimicrobial therapy, particularly when microbiological confirmation is pending or inconclusive despite high clinical suspicion.

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