Most genetic susceptibility to cutaneous melanoma remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 cases of melanoma (67% newly genotyped) and 375,188 controls identified 54 significant (P < 5 × 10−8) loci with 68 independent single nucleotide polymorphisms. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with GWAS of nevus count and hair color, and transcriptome association approaches, uncovered 31 potential secondary loci for a total of 85 cutaneous melanoma susceptibility loci. These findings provide insights into cutaneous melanoma genetic architecture, reinforcing the importance of nevogenesis, pigmentation and telomere maintenance, together with identifying potential new pathways for cutaneous melanoma pathogenesis.
Genome-wide summary statistics for the confirmed meta-analysis have been made publicly available at dbGaP (phs001868.v1.p1), with the exclusion of self-reported data from 23andMe and UK Biobank. Results for SNPs with a fixed or random P < 5 × 10−7 from the total meta-analysis are reported in Supplementary Table 7. The total meta-analysis includes self-reported cutaneous melanoma GWAS data from the UK Biobank and 23andMe. The raw genetic and phenotypic UK Biobank data used in this study, which were used under license, are available from: http://www.ukbiobank.ac.uk/. The genome-wide summary statistics from 23andMe data were obtained under a data transfer agreement. Further information about obtaining access to the 23andMe summary statistics is available from https://research.23andme.com/collaborate/. Source data for Fig. 2, Extended Data Figs. 4–6 and Supplementary Figs. 2 and 3 are available with the paper.
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NCI: This study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH) and Department of Health and Human Services (DHHS). AOCS/OCAC/SEARCH: AOCS/OCAC/SEARCH is accessible via European Genome–Phenome Archive. We acknowledge their support and data, and the contribution of the study nurses, research assistants and all clinical and scientific collaborators in generation of these data. We also acknowledge their funding sources: OCAC (NIH grant no. U19CA148112), SEARCH team (Cancer Research UK grant no.C490/A16561), AOCS (US Army Medical Research and Material Command under grant no. DAMD17‐01‐1‐0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Foundation of Western Australia, The Cancer Council Tasmania and the National Health and Medical Research Council of Australia (NHMRC) (grant nos. ID400413 and ID400281, as well as support from S. Boldeman, the Agar family, Ovarian Cancer Action (UK), Ovarian Cancer Australia and the Peter MacCallum Foundation). MelaNostrum Consortium: We thank the participants of the MelaNostrum Consortium from Italy (Genoa, L’Aquila, Rome, Padua, Milan, Florence and Bergamo), Spain (Valencia and Barcelona), Greece (Athens) and Cyprus (Nicosia) who provided data and biospecimens for this study. The Consortium is partially supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, NCI, NIH, DHHS. Funding for the University of Genoa and Genetics of Rare Cancers, Ospedale Policlinico San Martino came from Italian Ministry of Health 5 × 1000 per la Ricerca Corrente to Ospedale Policlinico San Martino and AIRC IG 15460. The research at the Melanoma Unit in Barcelona was supported by the Spanish Fondo de Investigaciones Sanitarias grant nos. PI15/00716 and PI15/00956 cofinanced by FEDER ‘Una manera de hacer Europa’; CIBER de Enfermedades Raras of the Instituto de Salud Carlos III, Spain, cofinanced by European Development Regional Fund ‘A way to achieve Europe’ ERDF; AGAUR 2014_SGR_603 of the Catalan Government, Spain; European Commission, contract no. LSHC-CT-2006-018702 (GenoMEL) and by the European Commission under the 7th Framework Programme, Diagnostics; ‘Fundació La Marató de TV3’ grant no. 201331-30, Catalonia, Spain; ‘Fundación Científica de la Asociación Española Contra el Cáncer’ grant no. GCB15152978SOEN, Spain, and CERCA Programme/Generalitat de Catalunya. Melanoma research at the Department of Dermatology, University of L’Aquila, Italy was supported by the Italian Ministry of the University and Scientific Research (PRIN-2012 grant no. 2012JJX494). Q-MEGA/QTWIN: The Q-MEGA/QTWIN study was supported by the Melanoma Research Alliance, the NIH NCI (grant nos. CA88363, CA83115, CA122838, CA87969, CA055075, CA100264, CA133996 and CA49449), the NHMRC (grant nos. 200071, 241944, 339462, 380385, 389927, 389875, 389891, 389892,389938, 443036, 442915, 442981, 496610, 496675, 496739, 552485, 552498 and APP1049894), the Cancer Councils New South Wales, Victoria and Queensland, the Cancer Institute New South Wales, the Cooperative Research Centre for Discovery of Genes for Common Human Diseases, Cerylid Biosciences (Melbourne), the Australian Cancer Research Foundation, The Wellcome Trust (grant no. WT084766/Z/08/Z) and donations from N. and S. Hawkins. S. MacGregor acknowledges fellowship support from the Australian National Health and Medical Research Council and from the Australian Research Council.
Please see the Supplementary Note for additional acknowledgments.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Quantile-Quantile plot of total CM meta-analysis.
Quantile-quantile plots of negative log10 two-sided P value derived from a fixed-effects inverse-variance weighted meta-analysis of log(OR) effect-sizes derived from the logistic regression GWAS listed in Supplementary Table 1. All confirmed and self-report cases are included, with a total sample size of 36,760 melanoma cases and 375,188 controls.
Extended Data Fig. 2 Manhattan plots of melanoma risk loci from total and confirmed-only GWAS meta-analyses.
Negative log10 two-sided P value derived from a fixed-effects inverse-variance weighted meta-analysis of log(OR) effect-sizes derived from the logistic regression GWAS (y-axis) are plotted by their chromosome position. The confirmed-only analysis included 30,134 cases with histopathologically confirmed CM, and 81,415 controls. The total CM meta-analysis includes all confirmed and self-report cases, with a total sample size of 36,760 CM cases and 375,188 controls. Multiple-testing corrected genome-wide significance threshold was P<5×10−8. We display in order the total CM meta-analysis without limiting the y-axis; the pathologically confirmed CM cases only meta-analysis with the y-axis limited to 1×10−25 and without a limit to more clearly display loci other than MC1R.
Extended Data Fig. 3 Quantile-Quantile plot of confirmed-only CM meta-analysis.
Quantile-quantile plots of negative log10 two-sided P value derived from a fixed-effects inverse-variance weighted meta-analysis of log(OR) effect-sizes derived from the logistic regression GWAS listed in Supplementary Table 1. Only cases with histopathologically confirmed CM are included, with a total sample size of 30,134 melanoma cases and 81,415 controls.
Extended Data Fig. 4 Distribution of pigmentation polygenic risk scores across melanoma histological subtypes.
The figure shows whether PRS defined based on SNPs associated with hair color differ across CM histological types (Methods; SSM: superficial spreading melanoma; NM: nodular melanoma; LM: lentigo melanoma; Acral: acral lentiginous melanoma). The higher the PRS the lighter the hair color. When comparing subtype 1 vs. subtype 2, we report the effect size for the linear regression of PRS on subtype 1, including study and principal components as covariates to control for population stratification. The regression coefficient, 95% confidence interval, and statistical significance are shown. The positive beta indicates the PRS is higher in subtype 2 (for example, nonacral melanomas). This analysis included 9828 SSM, 2137 NM, 900 LM, 353 acral melanoma cases and 44676 controls. Two-sided t-statistic was used for testing significance. P values reported were not adjusted for multiple comparison. Source data
Extended Data Fig. 5 LD score regression plots.
LD score regression was performed for the top 4000 (A) 2000 (B) and 1000 (C) tissue-specific genes from melanocyte and GTEx tissue types (v7 datasets), to assess the enrichment of melanoma heritability in these genomic regions using summary statistics from Total CM GWAS meta-analysis. The level of enrichment and P values are shown, with an FDR = 0.05 cutoff marked as a dashed horizontal line (See Methods for statistical test). Tissue categories are color-coded, and a subset of top individual tissue types are shown on the plot. Tissue types from “Skin” category including melanocytes are highlighted in magenta. Source data
Extended Data Fig. 6 Effect sizes for confirmed-only meta-analysis versus UKBB self-report set.
For each independent genome-wide significant (P<5×10−8) lead SNP from the confirmed-only meta-analysis (30,134 melanoma cases and 81,415 controls), we plot on the Y-axis UK Biobank self-report GWAS (UKBB SR) log(OR) and standard error from a logistic regression GWAS (1,802 self-report CM cases and 7,208 controls) and on the X-axis we plot the log(OR) and standard error from a fixed-effects inverse-variance weighted meta-analysis of log(OR) effect-sizes derived from the logistic regression GWAS for confirmed melanoma cases listed in Supplementary Table 1. We also report the r2 correlation from the linear regression of UKBB SR log(OR) on the confirmed met-analysis estimates, weighted by their standard error. Source data
Supplementary Note and Figs. 1–9
Supplementary Data 1
P value and regional LD for each lead SNP from Supplementary Table 3. Regional association P values and LD patterns for identified CM susceptibility regions. Top panel plots –log10 association P values from the total CM fixed-effects meta-analysis. Blue dot is the most significant regional variant and points above blue line indicate association P < 5× 10−8. Darker shades of red indicate higher LD with most significant regional variant. Bottom panel displays nearby genes. Legend applies to all subsequent plots.
Source Data Fig. 2
Statistical Source Data for Figure 2: Overlap of loci identified by primary and secondary analyses. Positions for each locus and 0,1 value for detected in the listed analyses as per Fig. 2.
Source Data Extended Data Fig. 4
Statistical source data
Source Data Extended Data Fig. 5
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Source Data Extended Data Fig. 6
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Source Data Supplementary Fig. 2
Statistical source data. A1 is the effect allele for the listed BETA etc.
Source Data Supplementary Fig. 3
Statistical source data
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Landi, M.T., Bishop, D.T., MacGregor, S. et al. Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility. Nat Genet 52, 494–504 (2020). https://doi.org/10.1038/s41588-020-0611-8
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