Methods

1. Introduction

The incidence of cutaneous melanoma (CM) has increased at a rapid pace among the populations of European descent over the past five decades; metastatic melanoma now represents the leading cause of death from skin cancer (Jemal, 2009; MacKie, 2009). Since early disease is largely curable, identification of high risk individuals with an eye towards preventive measures may reduce deaths from melanoma. CM susceptibility is likely to be governed by an interplay of environmental factors, e.g. excessive sun exposure (Tucker, 2003), and genetically determined phenotypic traits, such as nevus propensity, red or blonde hair, blue or green eyes, fair skin and limited tanning ability (Gandini, 2005). Recent genome-wide association studies (GWAS) have described additional genetic loci in pathways that regulate cutaneous pigmentation or nevus development.
Within the last 15 years, ~150 genetic association studies have been published for CM including two CM-GWAS (Bishop, 2009; Brown, 2008), claiming or refuting association with putative melanoma genes. This extensive amount of information is increasingly difficult to follow, assess, and interpret. We have therefore collected and catalogued all genetic association studies published in the field of CM, and performed systematic meta-analyses for all eligible polymorphism as has been done for other diseases (Lill, 2010; Castaldi, 2010; Dolan, 2010; Vineis, 2009; Allen, 2008; Bertram, 2007). In addition, we have applied the Venice criteria, interim guidelines developed by the Human Genome Epidemiology (HuGENet), to evaluate the epidemiologic validity of nominally significant meta-analysis results. The results of this field synopsis, including detailed summaries of all association studies and meta-analysis results, have been posted on a dedicated, regularly updated, freely available online database (http://www.melgene.org), that currently highlights the most prominent genetic loci showing Database Organization and Methods.

Overview

The goal of the MelGene database is to serve as a comprehensive, unbiased, publicly available and regularly updated collection of published genetic association studies performed on CM. Eligible publications are identified following systematic searches of scientific literature databases [PubMed database (National Center for Biotechnology Information; NCBI, http://www.ncbi.nlm.nih.gov/pubmed); the HuGE Navigator (http://www.hugenavigator.net) and the MMMP (Melanoma Molecular Maps Project, http://www.mmmp.org/MMMP]. Data selected for display summarize key characteristics of the investigated study cohorts (e.g., gene overview), as well as genotype distributions in cases and controls (e.g., polymorphism details). For polymorphisms with genotype data in at least four case-control samples, continuously updated random-effects meta-analyses are presented (see meta-analysis methods). Note that data obtained from family-based studies are not included in the meta-analyses, as crude odds ratios cannot be readily calculated from overall genotype distributions. However, these studies and their qualitative results are still listed on the gene-summary pages of the MelGene website. To ensure the highest degree of scientific objectivity, only studies published in peer-reviewed journals available in English are considered for inclusion into the database. In particular, this precludes the inclusion of data presented only in abstracted form, e.g. at scientific meetings. We encourage authors of original reports fulfilling the above criteria to submit their data as soon as their work is accepted for publication.

Meta-Analysis Methods

For all variants with at least four independent case-control datasets available, we calculated study-specific crude ORs and 95% confidence intervals (CIs) using allelic contrasts (usually minor versus major allele based on allele frequencies in healthy controls) and performed random-effects allelic meta-analyses (DerSimonian, 1986). This procedure is done including all studies irrespective of ethnicity (denoted by "All studies" on the meta-analysis figures), and repeated after exclusion of the initial study ("All excl initial"), after exclusion of studies in which a deviation of Hardy-Weinberg Equilibrium (HWE) was detected in controls ("All excl HWE deviations"). In addition, ethnicity-specific meta-analyses are performed whenever genotype data is available from at least three independent case-control populations. Visually, the results of these meta-analyses are displayed for each polymorphism in form of forest plots. Overlapping samples (of which usually only the largest is included), studies with missing data, or control samples deviating from HWE are indicated on these graphs. Note that when only a few studies are included in the meta-analyses (i.e. less than ~10), the random effects model may yield summary ORs and confidence bounds that are slightly anti-conservative.
Along with the forest plots, which depict summary ORs only for the most current set of available data, the results of cumulative meta-analyses are displayed for each polymorphism with data available in at least four independent case-control datasets. These graphs display summary ORs (for the "All studies" paradigm using the same allele-based random-effects analyses as outlined above) recalculated after each study. Thus, these graphs allow an evaluation of the estimated summary effects over time. Note that the most current summary OR (listed at the very top of the cumulative meta-analysis plots) is identical to the corresponding summary OR depicted on the forest plots (see above).
Inclusion of Genome-wide Association Studies (GWAS) and GWAS Replication Studies In the absence of publicly available datasets from CM-GWAS we extracted data from all polymorphisms reported in the original GWAS publications, i.e. allele frequencies or per-allele odds ratio, and included them in the MelGene meta-analyses where applicable. We also included data from replication studies on selected variants derived from GWAS of traits relevant to CM susceptibility, i.e. hair/eye/skin pigmentation, basal cell carcinoma or melanocytic nevus. For inclusion of GWAS and GWAS replication data of related traits which only provided allelic ORs and CIs, we "estimated" genotype summary counts based on the ORs/CIs for the purpose of the Venice grading, thus they are only approximate numbers of the real genotype counts.

2. The "Top Results" List

In an effort to facilitate the identification of the most promising meta-analysis results available in MelGene, a continuously updated list displaying the most strongly associated genes ("Top Results") has been added to the MelGene homepage. The list includes genes/loci which contain at least one variant showing a nominally significant summary OR in the analysis of all studies ("All"), or those limited to samples of a specific ethnicity (e.g. "Caucasian"). The nominally significant meta-analyses are then graded based on interim guidelines "Venice criteria" for the grading of the epidemiological credibility of genetic association studies recently developed by the Human Genome Epidemiology Network (HuGENet; Ioannidis, 2008). In the "Top Results" list, genes are ranked based on statistical significance (P value). For genes with more than one polymorphism showing nominally significant association, ranking is based on the best statistical meta-analysis result per gene. While we believe that this list represents an up-to-date summary of particularly promising CM candidate genes that warrant follow-up with high priority, we note that many of these may still represent false-positive findings.

HuGENet "Venice criteria"

We rate overall epidemiological credibility as strong if associations received three A grades, moderate if they received at least one B grade but no C grades, and weak if they received a C grade in any of the three assessment criteria. Current Venice rating of the MelGene top results can be found here.
Briefly, each meta-analyzed association in MelGene is graded on the basis of the amount of evidence, consistency of replication, and protection from bias. For amount of evidence, we assign the grade A when the total number of minor alleles of cases and controls combined in the meta-analyses exceeds 1,000, B when it is between 100 and 1,000, and C when it is less than 100. For consistency of replication, we assign the grade C for I2 point estimates < 25%, B for I2 values of 25-50%, and C for I2 values >50%. Note that this criterion does not apply to meta-analyses with a P-value < 1x10-7 after exclusion of the initial studie(s), as described in Khoury, 2009. For protection from bias, the guidelines propose consideration of various potential sources of bias, including errors in phenotypes, genotypes, confounding (population stratification) and errors or biases at the meta-analysis level (publication and other selection biases). A grade A implies that there is probably no bias that can affect the presence of the association, grade B that there is no demonstrable bias but important information is missing for its appraisal, and grade C that there is evidence for potential or clear bias that can invalidate the association. Errors and biases are also considered in the framework of the observed summary OR. Whenever the summary OR deviates less than 1.15-fold from the null in meta-analyses based on published data, we acknowledge that occult publication and selective reporting biases alone may invalidate the association, regardless of the presence or absence of other biases, and therefore assign a grade of C. When the summary OR deviates more than 1.15-fold from the null, we assign a grade of C when the modified regression test or excess test suggest the possibility of publication-bias or significance-chasing bias or when the association is no longer nominally statistically significant upon exclusion of the initial study or studies violating HWE.

References

Jemal A, Siegel R, Ward E, Hao Y, Xu J, Thun MJ. Cancer statistics, 2009. CA Cancer J Clin. 2009; 59(4):225-49.

MacKie RM, Hauschild A, Eggermont AM. Epidemiology of invasive cutaneous melanoma. Ann Oncol. 2009; 20 Suppl 6:vi1-7.

Tucker MA, Goldstein AM. Melanoma etiology: where are we? Oncogene. 2003; 22(20):3042-52.

Gandini S, Sera F, Cattaruzza MS, Pasquini P, Zanetti R, Masini C, Boyle P, Melchi CF. Meta-analysis of risk factors for cutaneous melanoma: III. Family history, actinic damage and phenotypic factors. Eur J Cancer. 2005; 41(14):2040-59.

Gandini S, Sera F, Cattaruzza MS, Pasquini P, Abeni D, Boyle P, Melchi CF. Meta-analysis of risk factors for cutaneous melanoma: I. Common and atypical naevi. Eur J Cancer. 2005; 41(1):28-44

Bishop DT, Demenais F, Iles MM, Harland M, Taylor JC, Corda E, Randerson-Moor J, Aitken JF, Avril MF, Azizi E, Bakker B, Bianchi-Scarra G, Bressac-de Paillerets B, Calista D, Cannon-Albright LA, Chin-A-Woeng T, Debniak T, Galore-Haskel G, Ghiorzo P, Gut I, Hansson J, Hocevar M, Hoiom V, Hopper JL, Ingvar C, Kanetsky PA, Kefford RF, Landi MT, Lang J, Lubi?ski J, Mackie R, Malvehy J, Mann GJ, Martin NG, Montgomery GW, van Nieuwpoort FA, Novakovic S, Olsson H, Puig S, Weiss M, van Workum W, Zelenika D, Brown KM, Goldstein AM, Gillanders EM, Boland A, Galan P, Elder DE, Gruis NA, Hayward NK, Lathrop GM, Barrett JH, Bishop JA. Genome-wide association study identifies three loci associated with melanoma risk. Nat Genet. 2009; 41(8):920-5.

Brown KM, Macgregor S, Montgomery GW, Craig DW, Zhao ZZ, Iyadurai K, Henders AK, Homer N, Campbell MJ, Stark M, Thomas S, Schmid H, Holland EA, Gillanders EM, Duffy DL, Maskiell JA, Jetann J, Ferguson M, Stephan DA, Cust AE, Whiteman D, Green A, Olsson H, Puig S, Ghiorzo P, Hansson J, Demenais F, Goldstein AM, Gruis NA, Elder DE, Bishop JN, Kefford RF, Giles GG, Armstrong BK, Aitken JF, Hopper JL, Martin NG, Trent JM, Mann GJ, Hayward NK. Common sequence variants on 20q11.22 confer melanoma susceptibility. Nat Genet. 2008; 40(7):838-40.

Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet. 2007; 39(1):17-23.

Allen NC, Bagade S, McQueen MB, Ioannidis JP, Kavvoura FK, Khoury MJ, Tanzi RE, Bertram L. Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nat Genet. 2008; 40(7):827-34.

Lill CM, Roehr JT, McQueen MB, Bagade S, Kavvoura F, Schjeide BMM, Allen NC, Tanzi R, Khoury MJ, Ioannidis JPA, Bertram L. The PDGene Database. Alzheimer Research Forum. Available at: http://www.pdgene.org/.

Castaldi PJ, Cho MH, Cohn M, Langerman F, Moran S, Tarragona N, Moukhachen H, Venugopal R, Hasimja D, Kao E, Wallace B, Hersh CP, Bagade S, Bertram L, Silverman EK, Trikalinos TA. The COPD genetic association compendium: a comprehensive online database of COPD genetic associations. Hum Mol Genet. 2010; 19(3):526-34.

Vineis P, Manuguerra M, Kavvoura FK, Guarrera S, Allione A, Rosa F, Di Gregorio A, Polidoro S, Saletta F, Ioannidis JP, Matullo G. A field synopsis on low-penetrance variants in DNA repairs genes and cancer susceptibility. J Natl Cancer Inst. 2009; 101(1):24-36.

Dolan SM, Hollegaard MV, Merialdi M, Betran AP, Allen T, Abelow C, Nace J, Lin BK, Khoury MJ, Ioannidis JP, Bagade S, Zheng X, Dubin RA, Bertram L, Velez Edwards DR, Menon R. Synopsis of Preterm Birth Genetic Association Studies: The Preterm Birth Genetics Knowledge Base (PTBGene). Public Health Genomics. 2010

Ioannidis JP, Boffetta P, Little J, O Brien TR, Uitterlinden AG, Vineis P, Balding DJ, Chokkalingam A, Dolan SM, Flanders WD, Higgins JP, McCarthy MI, McDermott DH, Page GP, Rebbeck TR, Seminara D, Khoury MJ. Assessment of cumulative evidence on genetic associations: interim guidelines. Int J Epidemiol. 2008 Feb; 37(1):120-32.

DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986; 7(3):177-88.

Khoury MJ, Bertram L, Boffetta P, Butterworth AS, Chanock SJ, Dolan SM, Fortier I, Garcia-Closas M, Gwinn M, Higgins JP, Janssens AC, Ostell J, Owen RP, Pagon RA, Rebbeck TR, Rothman N, Bernstein JL, Burton PR, Campbell H, Chockalingam A, Furberg H, Little J, O Brien TR, Seminara D, Vineis P, Winn DM, Yu W, Ioannidis JP. Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases. Am J Epidemiol. 2009; 170(3):269-79

Top Melgene Results

Gene 1: CLPTM1L

Gene 2: TYRP1

Gene 3: MTAP

Gene 4: CDKN2A

Gene 5: OCA2

Gene 6: MYH7B

Gene 7: SLC45A2

Gene 8: PLA2G6

Gene 9: MX2

Gene 10: VDR

Gene 11: FTO

Gene 12: CCND1

Gene 13: MITF

Gene 14: TYR

Gene 15: CDK10

Gene 16: AFG3L1

Gene 17: XPG

Gene 18: ATM

Gene 19: CASP8

Gene 20: PARP1

MelGene Statistics

Studies
192

Genes
280

Polymorphisms
1,114

Meta-analyses
79

How to Cite

1. Emmanouil Athanasiadis, Antonopoulou Kyriaki, Chatzinasiou Foteini, Christina Lill, Marilena Bourdakou, Argiris Sakellariou, Katerina Kypreou, Irene Stefanaki, Evangelos Evangelou, John Ioannidis, Lars Bertram, Alexander Stratigos and George Spyrou. (2014) A Web-based database of genetic association studies in cutaneous melanoma enhanced with network-driven data exploration tools. Database, Vol. 2014: article ID bau101; doi:10.1093/database/bau101.

2. Kyriaki Antonopoulou, Irene Stefanaki, Christina M Lill, Foteini Chatzinasiou, Katerina Kypreou, Fani Karagianni, Emmanouil Athanasiadis, George M Spyrou, John P A Ioannidis, Lars Bertram, Evangelos Evangelou and Alexander J Stratigos. (2014) Updated Field Synopsis and Systematic Meta-Analyses of Genetic Association Studies in Cutaneous Melanoma: The MelGene Database, J Invest Dermatol, doi:10.1038/jid.2014.491 .

3. Foteini Chatzinasiou, Christina M. Lill, Katerina Kypreou, Irene Stefanaki, Vasiliki Nicolaou, George Spyrou, Evangelos Evangelou, Johannes T. Roehr, Elizabeth Kodela, Andreas Katsambas, Hensin Tsao, John P.A. Ioannidis, Lars Bertram, Alexander J. Stratigos. (2011) Comprehensive Field Synopsis and Systematic Meta-analyses of Genetic Association Studies in Cutaneous Melanoma, J Natl Cancer Inst 103:1-9.