Independent effects of genetic risk, socioeconomic status, and lifestyle factors in melanoma: A large-scale gene-environment analysis

Background: Melanoma is the 5th most common cancer with an increasing incidence in the younger population. Prior literatures have shown that melanoma incidence paradoxically increases with socioeconomic affluence. Yet, the mechanisms underlying this pattern remains unclear. Prior gene-environment studies have focused primarily on sun exposure and phenotypic traits, with socioeconomic context largely unexplored. Our study integrates genetic, socioeconomic, and lifestyle data from the United Kingdom Biobank (UKBB) to disentangle the independent and joint effects of genetic risk and socioeconomic factors on melanoma incidence. Methods: We analyzed 303,880 UKBB participants using Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident melanoma in an unrelated White British ancestry. We adjusted for sex, body mass index, smoking, skin color, alcohol intake frequency, vitamin D levels, sun-protection behavior, and assessment center (proxy for home location). We modelled the effects of the Index of Multiple Deprivation (IMD) by quartiles and polygenic risk score (PRS) on incident melanoma: IMD and PRS independently, additive model (IMD + PRS), and an interaction model (IMD × PRS). Results: In the IMD-only model, compared to the least deprived (Q1), participants in Q3 and Q4 had significantly lower risk of melanoma incidence (Q3: HR = 0.84 [95% CI = 0.72 - 0.98]; Q4: HR = 0.84, [95% CI = 0.71 - 1.00]). In the PRS-only model, each unit increase in PRS was associated with a 2.16-fold increased melanoma risk (HR = 2.16 [95% CI = 1.99 - 2.34]). In the additive model, PRS and IMD effect remained largely unchanged. The interaction model showed no evidence of IMD-PRS interaction (HR 1.0; p > 0.6). Conclusions: Greater genetic susceptibility and higher socioeconomic status was associated with increased melanoma risk through independent and non-interacting pathways. Even after accounting for lifestyle factors, socioeconomic differences remained, suggesting that melanoma risk is shaped by factors extending beyond individual lifestyle and behavior. Our findings highlight that there is no evidence that socioeconomic disparities reflect differences in genetic susceptibility, reinforcing the need for prevention and early detection strategies that address both inherited risk and social and structural contexts.