Objective:A two-sample bidirectional Mendelian randomization (MR) analysis was used to analyze the risk factors related to sunburn.Methods:Data were downloaded from the Gene-Wide Association Studies (GWAS) of the IEU Open GWAS project, and a two-sample bidirectional MR was conducted. In the forward MR analysis, the exposure factors were skin color, ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, urticaria, and education attainment, while the outcome factor was sunburn. In the reverse MR analysis, the exposure factor was sunburn, while the outcome factors were skin color, ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, urticaria, and education attainment. The data were analyzed using the "TwoSampleMR" package in R version 4.2.3. The result of the MR analysis were interpreted using the odds ratio ( OR) and the corresponding 95% confidence interval (95% CI), and a P-value <0.05 was considered statistically significant. In the analysis, we set a significance threshold of P-value<5×10 -8 (if sufficient instrumental variables cannot be obtained, the threshold will be adjusted to P-value<5×10 -6), eliminated linkage disequilibrium (with R2<0.001 and within a regional range of 10 000 kb), and screened single nucleotide polymorphisms (SNPs) that were significantly related to the research content, which would be set in the analysis as instrumental variables (IVs). For eligible IVs, a MR was conducted using the MR Egger, Weighted median, Inverse variance weighted (IVW), Simple mode, and Weighted mode method to explore the causal relationships between sunburn and various factors. The result obtained by the IVW method were taken as the main outcome indicator and summarized into a forest plot, while other method were used to supplement the IVW result. The heterogeneity of the IVs was evaluated by the Cochran Q-test. The direction of the causal effect and heterogeneity were evaluated through the scatter plot. The sensitivity of the result was analyzed by the leave-one-out test. The funnel plot was used to assess the potential bias. Results:9 851 867 SNPs related to skin color, 9 851 867 SNPs related to ease of skin tanning, 11 972 414 SNPs related to skin pigmentation, 9 851 867 SNPs related to facial aging, 16 121 213 SNPs related to atopic dermatitis, 24 191 078 SNPs related to contact dermatitis, 24 187 496 SNPs related to urticaria, 11 972 619 SNPs related to education attainment were obtained from the GWAS database. A total of 11 976 212 SNPs were obtained from the sunburn dataset. In the forward MR analysis, the IVW result showed a significant negative correlation between skin color and sunburn ( OR=0.68, 95% CI: 0.66-0.70, P<0.001); and a significant positive correlation between the ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, education attainment, and sunburn (ease of skin tanning: OR=1.30, 95% CI: 1.29-1.32, P<0.001; skin pigmentation: OR=1.76, 95% CI: 1.66-1.87, P<0.001; facial aging: OR=2.25, 95% CI: 1.67-3.04, P<0.001; atopic dermatitis: OR=1.02, 95% CI: 1.00-1.03, P=0.010; contact dermatitis: OR=1.01, 95% CI: 1.00-1.01, P=0.031; education attainment: OR=1.29, 95% CI: 1.22-1.36, P<0.001); while urticaria was not statistically significant ( P=0.056). The Cochran Q-test and scatter plot showed that there was a significant negative correlation between skin color and sunburn and a positive correlations between the ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, education attainment and sunburn. There was some heterogeneity among the IVs in research. The result of the leave-one-out test showed that no SNPs had a distinct impact on the causal effect, and the result of the forward MR analysis were relatively stable. The result of the funnel plot showed that the included SNPs were symmetrically distributed, and there was no potential bias in the result. In the reverse MR analysis, the IVW result showed a significant negative correlation between sunburn and skin color ( OR=0.16, 95% CI: 0.12-0.21, P<0.001); and a significant positive correlation between sunburn and ease of skin tanning, skin pigmentation, facial aging (ease of skin tanning: OR=26.78, 95% CI: 20.52-34.93, P<0.001; skin pigmentation: OR=3.12, 95% CI: 2.57-3.78, P<0.001; facial aging: OR=1.30, 95% CI: 1.24-1.37, P<0.001); while atopic dermatitis ( P=0.477), contact dermatitis ( P=0.318), urticaria ( P=0.328) and education attainment ( P=0.627) as outcome factors were not statistically significant. The Cochran Q-test and scatter plot showed that there was a significant negative correlation between sunburn and skin color and a positive correlations between sunburn and ease of skin tanning, skin pigmentation, facial aging. There was some heterogeneity among the IVs in research. The result of the leave-one-out test showed that no SNPs had a distinct impact on the causal effect, and the result of the reverse MR analysis were relatively stable. The result of the funnel plot showed that the included SNPs were symmetrically distributed, and there was no potential bias in the result . Conclusions:Skin color and sunburn are protective factors against each other; ease of skin tanning, skin pigmentation, and facial aging are bidirectional risk factors of sunburn; atopic dermatitis, contact dermatitis, and education attainment are risk factors of sunburn.

Objective:A two-sample bidirectional Mendelian randomization (MR) analysis was used to analyze the risk factors related to sunburn.Methods:Data were downloaded from the Gene-Wide Association Studies (GWAS) of the IEU Open GWAS project, and a two-sample bidirectional MR was conducted. In the forward MR analysis, the exposure factors were skin color, ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, urticaria, and education attainment, while the outcome factor was sunburn. In the reverse MR analysis, the exposure factor was sunburn, while the outcome factors were skin color, ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, urticaria, and education attainment. The data were analyzed using the "TwoSampleMR" package in R version 4.2.3. The result of the MR analysis were interpreted using the odds ratio ( OR) and the corresponding 95% confidence interval (95% CI), and a P-value <0.05 was considered statistically significant. In the analysis, we set a significance threshold of P-value<5×10 -8 (if sufficient instrumental variables cannot be obtained, the threshold will be adjusted to P-value<5×10 -6), eliminated linkage disequilibrium (with R2<0.001 and within a regional range of 10 000 kb), and screened single nucleotide polymorphisms (SNPs) that were significantly related to the research content, which would be set in the analysis as instrumental variables (IVs). For eligible IVs, a MR was conducted using the MR Egger, Weighted median, Inverse variance weighted (IVW), Simple mode, and Weighted mode method to explore the causal relationships between sunburn and various factors. The result obtained by the IVW method were taken as the main outcome indicator and summarized into a forest plot, while other method were used to supplement the IVW result. The heterogeneity of the IVs was evaluated by the Cochran Q-test. The direction of the causal effect and heterogeneity were evaluated through the scatter plot. The sensitivity of the result was analyzed by the leave-one-out test. The funnel plot was used to assess the potential bias. Results:9 851 867 SNPs related to skin color, 9 851 867 SNPs related to ease of skin tanning, 11 972 414 SNPs related to skin pigmentation, 9 851 867 SNPs related to facial aging, 16 121 213 SNPs related to atopic dermatitis, 24 191 078 SNPs related to contact dermatitis, 24 187 496 SNPs related to urticaria, 11 972 619 SNPs related to education attainment were obtained from the GWAS database. A total of 11 976 212 SNPs were obtained from the sunburn dataset. In the forward MR analysis, the IVW result showed a significant negative correlation between skin color and sunburn ( OR=0.68, 95% CI: 0.66-0.70, P<0.001); and a significant positive correlation between the ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, education attainment, and sunburn (ease of skin tanning: OR=1.30, 95% CI: 1.29-1.32, P<0.001; skin pigmentation: OR=1.76, 95% CI: 1.66-1.87, P<0.001; facial aging: OR=2.25, 95% CI: 1.67-3.04, P<0.001; atopic dermatitis: OR=1.02, 95% CI: 1.00-1.03, P=0.010; contact dermatitis: OR=1.01, 95% CI: 1.00-1.01, P=0.031; education attainment: OR=1.29, 95% CI: 1.22-1.36, P<0.001); while urticaria was not statistically significant ( P=0.056). The Cochran Q-test and scatter plot showed that there was a significant negative correlation between skin color and sunburn and a positive correlations between the ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, education attainment and sunburn. There was some heterogeneity among the IVs in research. The result of the leave-one-out test showed that no SNPs had a distinct impact on the causal effect, and the result of the forward MR analysis were relatively stable. The result of the funnel plot showed that the included SNPs were symmetrically distributed, and there was no potential bias in the result. In the reverse MR analysis, the IVW result showed a significant negative correlation between sunburn and skin color ( OR=0.16, 95% CI: 0.12-0.21, P<0.001); and a significant positive correlation between sunburn and ease of skin tanning, skin pigmentation, facial aging (ease of skin tanning: OR=26.78, 95% CI: 20.52-34.93, P<0.001; skin pigmentation: OR=3.12, 95% CI: 2.57-3.78, P<0.001; facial aging: OR=1.30, 95% CI: 1.24-1.37, P<0.001); while atopic dermatitis ( P=0.477), contact dermatitis ( P=0.318), urticaria ( P=0.328) and education attainment ( P=0.627) as outcome factors were not statistically significant. The Cochran Q-test and scatter plot showed that there was a significant negative correlation between sunburn and skin color and a positive correlations between sunburn and ease of skin tanning, skin pigmentation, facial aging. There was some heterogeneity among the IVs in research. The result of the leave-one-out test showed that no SNPs had a distinct impact on the causal effect, and the result of the reverse MR analysis were relatively stable. The result of the funnel plot showed that the included SNPs were symmetrically distributed, and there was no potential bias in the result . Conclusions:Skin color and sunburn are protective factors against each other; ease of skin tanning, skin pigmentation, and facial aging are bidirectional risk factors of sunburn; atopic dermatitis, contact dermatitis, and education attainment are risk factors of sunburn.