Personalized Prediction of Cutaneous Melanoma Risk Based on Polymorphism of the Genes Related to Skin Aging, Phenotypic Characteristics, and Sun Exposure in Lithuania

Abstract

Background/Objectives: This is the first study in Eastern Europe to integrate skin and iris phenotypic characteristics with selected polymorphisms in genes related to skin aging, melanogenesis and skin pigmentation, and inflammatory regulation in relation to cutaneous melanoma (CM) risk. Methods: This case–control study included 180 patients with primary CM identified from the Hospital of the LSMU Kauno klinikos database and 181 controls without a personal history of skin cancer selected from a population-based study in Kaunas. All participants underwent dermatological and ophthalmological examinations and completed questionnaires assessing sun-exposure habits, including severe sunburn history, and Fitzpatrick skin phototype. The total-body number of common melanocytic nevi (CMN) >2 mm in diameter and the number of iris freckles were evaluated using standardized protocols. Five selected genetic polymorphisms, including TYR rs1126809, SLC45A2 rs26722, SLC45A2 rs16891982, IL6 rs1800795, and TNF-α rs1800629, were genotyped. Associations with CM were assessed using multivariable logistic regression. Results: We identified three phenotypical factors independently associated with increased odds of CM (OR; 95% CI): a total-body CMN count >15 (7.89; 4.29–14.53), ≥4 iris freckles (3.70; 2.04–6.74), and a history of severe sunburn (2.76; 1.50–5.07). Compared with Fitzpatrick skin phototype IV, phototypes II (0.35; 0.15–0.82) and III (0.28; 0.11–0.70) were associated with decreased CM odds. In the multivariable model the heterozygous SLC45A2 rs16891982 genotype was associated with increased CM odds (6.64; 1.48–29.83), while the IL6 rs1800795 Mono G genotype revealed an inverse association with CM (0.39; 0.16–0.97). Conclusions: A total-body CMN count >15, ≥4 iris freckles, and severe sunburn history revealed strong independent associations with increased CM risk. However, associations involving SLC45A2 rs16891982 and IL6 rs1800795 in this Lithuanian case–control study were model-dependent. These findings highlight the potential value of integrating selected genetic markers with phenotypic characteristics and sun-exposure history in the development of personalized CM risk prediction models; however, validation in larger populations is required.