Journal Logo


LINE-1 methylation in peripheral blood and the risk of melanoma in melanoma-prone families with and without CDKN2A mutations

Hyland, Paula L.a,b; Burke, Laura S.a; Pfeiffer, Ruth M.a; Mirabello, Lisaa; Tucker, Margaret A.a; Goldstein, Alisa M.a; Yang, Xiaohong R.a

Author Information
doi: 10.1097/CMR.0b013e32835adc51
  • Free



Cutaneous malignant melanoma (CMM) is a potentially fatal form of skin cancer with a heterogenous etiology 1. Established risk factors include the presence and number of dysplastic nevi (DN), pigmentation phenotype (blond or red hair color, light eye color, freckling, and skin sensitivity to the sun), and sun exposure 2. Approximately 10% of CMM cases occur in a familial setting 1,2. The cyclin-dependent kinase inhibitor 2A (CDKN2A) gene is the major high-risk melanoma susceptibility gene identified to date. Germline mutations of the CDKN2A gene have been described in ∼20% of familial melanoma kindreds 3,4. Although germline CDKN2A mutations are associated with a high risk of CMM, the penetrance of this gene is incomplete and varies by age and geographic location 5. Further, phenotypic manifestations such as age at diagnosis, presence/number of DN, number of melanomas, and cosegregation of pancreatic cancer vary significantly among mutation carriers even within a single family 1,4. These findings suggest that other factors may modify the effect of CDKN2A.

Compelling evidence indicates that epigenetic changes including DNA methylation play an important role in cancer risk and development. Global genomic DNA hypomethylation [i.e. the overall reduction of the 5-methylcytosine content (5-MeC)] is a frequent molecular event in cancer and is thought to contribute to carcinogenesis by inducing genome instability and chromosomal aberration 6–8. Large decreases in 5-MeC across the genome reflect, in part, changes in the methylation status of repetitive sequences. Long interspersed nucleotide element-1 (LINE-1) is a long terminal-repeat class of retroposons that is the most successfully integrated mobile element in the human genome and accounts for ∼20% of the human genome 9. Generally, reduced LINE-1 methylation levels have been associated with cancer 10,11. More recently, measures of LINE-1 methylation have been examined as potential phenotypic markers of cancer risk in peripheral blood or white blood cells. After adjusting for known risk factors, epidemiologic studies have reported associations between LINE-1 methylation in blood and human papilloma virus-positive cervical precancer 12 and several different cancers including cancers of the liver, kidney, head and neck, and testicular germ cells 11,13–15.

However, there are no data on the relationship between LINE-1 methylation in blood and the risk of familial melanoma. Therefore, the goal of this study was to evaluate whether the extent of methylation of the LINE-1 in peripheral blood mononuclear cells (PBMCs) was associated with CMM risk in melanoma-prone families with and without CDKN2A mutations.

Materials and methods

Study population

The study population of this family study has been previously described 16,17. In brief, US families with at least two living first-degree relatives with a history of invasive melanoma were ascertained through healthcare professionals or self-referrals. All participants willing to participate in the study underwent a full body skin examination to characterize phenotypes (type and total number of nevi, extent of freckling, skin complexion, evidence of solar injury, and hair and eye color) and completed risk factor questionnaires for sun-related exposures such as tanning ability. All diagnoses of melanoma were confirmed by histologic review of pathologic material and pathology reports. The study was approved by the National Cancer Institute Clinical Center Institutional Review Board and conducted according to the Declaration of Helsinki. Informed consent was obtained from all participants. The current study was based on 64 families (26 families segregating CDKN2A mutations and 38 families without known mutations). Controls included unaffected family members (n=100) and a small number of genetically unrelated spouses (n=23). CMM cases and controls with and without CDKN2A mutations were selected from families based on the availability of primary frozen PBMCs. All study participants were Caucasian, and the study population was comprised of 115 CMM cases (45 CDKN2A carriers and 70 noncarriers) and 123 controls (32 CDKN2A carriers and 91 noncarriers).

DNA extraction and LINE-1 methylation

Deterioration of DNA methylation levels in cultured PBMC samples has previously been reported 18. To avoid this problem, we extracted total genomic DNA directly from cryopreserved primary PBMC cells (3−5×106 cells) using Trizol (Sigma-Aldrich Corp., St. Louis, Missouri, USA) as per the manufacturers’ guidelines. All extracted DNA samples were run on a 0.8% agarose gel to assess integrity and purity, and concentration was determined using a NanoDrop (Thermo Scientific, Wilmington, Delaware, USA). The Zymo Research EZ Methylation Kit (Zymo Research, Irvine, California, USA) was used for bisulfite modification of 500–1000 ng of PBMC DNA and LINE-1 methylation analysis was carried out by EpigenDx (Worcester, Massachusetts, USA) 14,15. We examined the methylation status at four CpG sites in the LINE-1 promoter 13,15,19 (GenBank accession #: M80343, −605, −593, −590 and −583 bp from ATG of ORF1 15) (Supplementary Fig. 1a and b). The relative 5-MeC content was expressed as the percentage of methylated cytosines divided by the sum of methylated and unmethylated cytosines (5-MeC/[5-MeC+unmethylated cytosine]=%5-MeC) (Supplementary Fig. 1b). Methylation status at each of the four CpG loci were analyzed individually as a T/C SNP using QCpG software (Pyrosequencing Qiagen; Qiagen Inc., Valencia, California, USA) and then averaged together to provide a mean or overall %5-MeC or LINE-1 status. Validation of the LINE-1 assay (and the four CpG sites spanning the LINE-1 sequence) was carried out using bisulfite-modified methylated control DNA and nonmethylated control DNA (Supplementary Fig. 1c). Percent DNA methylation within LINE-1 was measured in triplicate for all samples and a coefficient of variation (CV) among blinded replicates (n=20) was used to determine intrabatch and interbatch variation. Following exclusion of individual runs with greater than 7.0% bisulfite unconverted cytosine values and samples with a CV greater than 10% (n=3), data were available on 235 samples (114 CMM cases and 121 controls).

Statistical analysis

χ2-Tests were used to examine the relationship between overall and site-specific LINE-1 methylation levels and demographic and CMM risk factors including age at blood draw, CDKN2A mutation status, number of moles, presence of DN, solar injury, melanocortin 1 receptor (MC1R) variants, tanning ability, skin type, eye color, and hair color among unaffected individuals. We defined tertiles of LINE-1 methylation using cut-points based on distributions among unaffected individuals. The tertiles were defined separately for men and women, as LINE-1 methylation varied by sex. To assess our main hypothesis, we estimated odds ratios (ORs) and 95% confidence intervals (95% CIs) for the association of the level of LINE-1 methylation with CMM status using unconditional logistic regression models, adjusting for age at blood draw (as a continuous variable). The highest tertile (T3) was used as the reference group as hypomethylation is generally considered as a risk category. Familial correlations were accounted for in the variance calculations using a generalized estimating equations approach 20. Associations were also evaluated separately in CDKN2A mutation-positive and CDKN2A mutation-negative families to assess effect modification by CDKN2A status. All tests were two sided. Data were analyzed using SAS statistical software, version 9.1 (SAS Institute, Cary, North Carolina, USA).


In total, there were 114 CMM cases and 121 unaffected individuals included in the analysis. CDKN2A carrier status, number of moles, DN, solar injury, MC1R genetic variation, tanning ability and skin type were significantly associated with the risk of CMM (Table 1).

Table 1
Table 1:
Distribution of age, sex,CDKN2A, pigmentation phenotype, and sun exposure variables in 64 melanoma-prone families by melanoma status

Among unaffected individuals, overall LINE-1 methylation was narrow in range (mean 78%, range 73.3–80.7%) and was similar to values previously reported for LINE-1 methylation in blood or leukocytes 14,21. Methylation levels varied slightly among controls across each of the four CpG sites sequenced, with the lowest mean methylation observed at CpG4 (mean=73.9%, SD=1.5) and the highest levels at CpG1 (mean=82.9%, SD=1.9). Male controls had significantly higher overall LINE-1 methylation levels (overall=78.5%) than female controls (overall=77.7%, P=0.0001) (Fig. 1). In general, overall or site-specific LINE-1 methylation were not significantly associated with age at blood draw or other CMM risk factors (Table 2), with the exception of site-specific methylation at CpG1, which showed a negative association with age at blood draw (P=0.01).

Fig. 1
Fig. 1:
Boxplot of meanLINE-1 methylation (%) in unaffected individuals by sex. Males were shown to have statistically significantly higher overall LINE-1 methylation levels (overall=78.5%) than females (overall=77.7%, P=0.0001). The P-value was calculated using the Kruskal–Wallis test to compare average methylation levels between unaffected male and female controls.
Table 2
Table 2:
Relationship between overallLINE-1 methylation levels and demographic or CMM risk factors among unaffected individuals

Also, although decreased overall and site-specific LINE-1 methylation levels were more frequent among CMM cases compared with unaffected individuals, the associations were not statistically significant (Table 3). In addition, there was no significant difference between overall LINE-1 methylation levels and risk of CMM when CDKN2A mutation-positive and CDKN2A mutation-negative families were analyzed separately (Table 4).

Table 3
Table 3:
Association betweenLINE-1 methylation and risk of CMM
Table 4
Table 4:
Association between overall (average)LINE-1 methylation and risk of CMM, stratified by CDKN2A status

As LINE-1 methylation levels varied by sex, we further examined the association between CMM status and overall LINE-1 methylation in sex-stratified analyses and we observed similar results in each sex group (for males, OR: 1.50, 95% CI: 0.49–4.55, P=0.48, comparing lowest to highest methylation tertile; for females, OR: 1.41, 95% CI: 0.66–3.01, P=0.38). To assess whether melanoma diagnosis and treatment affected LINE-1 methylation, we also restricted the analysis to CMM cases whose blood was drawn before CMM diagnosis and observed a similar result (OR: 1.00, 95% CI: 0.32–3.09, P=1.00, comparing lowest to highest tertile).


We evaluated global LINE-1 methylation in PBMCs from 235 individuals from 64 melanoma-prone families (26 families segregating CDKN2A mutations and 38 families without CDKN2A mutations). Overall, we did not find a significant association between LINE-1 methylation and CMM status in our analyses, either with all families combined or with CDKN2A-positive and CDKN2A-negative families analyzed separately.

In agreement with previous reports, we observed that sex but not age 13–15,22–25 was significantly related to the global methylation status of LINE-1 in PBMCs, with women more likely to have reduced overall LINE-1 methylation compared with men. The reason for this is not known, and while a difference in intake or metabolism of folate between men and women has been suggested 13, more recent evidence does not support diet accounting for this difference 23.

The most commonly recognized effects of global hypomethylation are to facilitate chromosomal instability and to control gene expression 6,7. Recent epigenetic evidence suggests that changes including reduced or increased methylation at LINE-1 DNA sequences in blood are associated with the risk of cervical precancer and a number of different cancers 11–15. Thus, changes in LINE-1 methylation appear to be detectable even in normal tissue far from precancerous and/or tumor sites.

We observed no significant association between overall or CpG site-specific LINE-1 methylation and CMM in our melanoma-prone families with and without CDKN2A mutations. Similarly, we did not observe any association between LINE-1 methylation in PBMCs and known CMM risk factors. Our findings are in line with two independent studies in breast cancer that have reported a null association between LINE-1 methylation in blood and breast cancer risk 21,26. However, our study was limited by small sample size as the cases and controls were collected from high-risk families. Thus, future studies with a large sample size or pooled analyses from multiple family studies are needed to confirm these results. Interestingly, site-specific LINE-1 methylation has been reported as a molecular marker for prognosis of sporadic CMM, but only from melanoma tumors explanted ex vivo and cultured in vitro19. In this study, as well as in previously published studies, LINE-1 methylation was used as a surrogate for global DNA methylation content. The measure of the methylation levels of the repetitive LINE-1 elements used in the present study represents a pool of LINE-1 repeats from the entire genome and an average measure of methylation across the genome. Phokaew et al. 10 reported that LINE-1 methylation can be influenced differentially depending on where the particular LINE-1 sequences are located in the genome. Thus, methylation levels of LINE-1 sequences among different loci can be different in normal cells and it may be possible that opposite and concurrent changes of hypomethylation and hypermethylation at different LINE-1s across the genome could offset each other and therefore may not be reflected in the average measure of global LINE-1 methylation.

Although our study is exploratory, to our knowledge this is the first report to evaluate global methylation of LINE-1 in blood from melanoma-prone families. In this study, assay replicates were highly correlated. Also, our families had well-annotated sun exposure and pigmentation data, were heavily genetically loaded, and were of Caucasian ethnicity. These latter variables allowed us to control for the influence of race and genetic background on global DNA methylation in blood. Evidence suggests that global LINE-1 methylation patterns can be hereditary 14 and that genetic variants can influence DNA methylation 27. To control for this influence on LINE-1 methylation we used genetic controls from our high-risk kindreds to investigate the association of LINE-1 methylation in blood and risk of CMM. We also used nongenetic (spouse) controls, and to increase the power we further combined these two groups in our analyses. Furthermore, we observed that overall LINE-1 methylation in genetic versus nongenetic controls (spouse controls) were not significantly different (P=0.14) suggesting that the nongenetic controls do not display a different methylation pattern which could affect the current finding of no difference in risk between familial-driven melanoma and LINE-1 hypomethylation. Furthermore, we evaluated global LINE-1 methylation directly from frozen PBMCs, thereby circumventing any potential influence or artifact on methylation levels by short-term culture of primary cells. Our families were, however, ascertained primarily through self-referral or physician-referral, which might affect the generalizability of the results.


We found no significant evidence that changes in global LINE-1 methylation in peripheral blood were associated with familial CMM risk irrespective of CDKN2A status in our melanoma-prone families. Whether the methylation status of other long terminal-repeat retroposons or loci-specific LINE-1 sequences across the genome are associated with CMM risk or CDKN2A germline mutations in melanoma-prone families remains to be investigated in future larger studies.


The authors are indebted to the participating families, whose generosity and cooperation have made their study possible. They also acknowledge Virginia Pichler, Deborah Zametkin, and Mary Fraser for their contributions to this work. This research was supported by the Intramural Research Program of the NIH, NCI, DCEG. Paula L. Hyland was funded by the Cancer Prevention Fellowship Program, Division of Cancer Prevention, NCI, Bethesda, USA and the Health and Social Care (HSC), Northern Ireland, UK.

Conflicts of interest

There are no conflicts of interest.


1. Goldstein AM, Tucker MA. Genetic epidemiology of cutaneous melanoma: a global perspective. Arch Dermatol. 2001;137:1493–1496
2. Tucker MA, Fraser MC, Goldstein AM, Struewing JP, King MA, Crawford JT, et al. A natural history of melanomas and dysplastic nevi: an atlas of lesions in melanoma-prone families. Cancer. 2002;94:3192–3209
3. Eliason MJ, Larson AA, Florell SR, Zone JJ, Cannon-Albright LA, Samlowski WE, et al. Population-based prevalence of CDKN2A mutations in Utah melanoma families. J Invest Dermatol. 2006;126:660–666
4. Goldstein AM. Familial melanoma, pancreatic cancer and germline CDKN2A mutations. Hum Mutat. 2004;23:630
5. Bishop DT, Demenais F, Goldstein AM, Bergman W, Bishop JN, Bressac-de Paillerets B, et al. Geographical variation in the penetrance of CDKN2A mutations for melanoma. J Natl Cancer Inst. 2002;94:894–903
6. Wilson AS, Power BE, Molloy PL. DNA hypomethylation and human diseases. Biochim Biophys Acta. 2007;1775:138–162
7. Esteller M, Herman JG. Cancers as an epigenetic disease: DNA methylation and chromatin alterations in human tumours. J Pathol. 2002;196:1–7
8. Kawakami K, Matsunoki A, Kaneko M, Saito K, Watanabe G, Minamoto T. Long interspersed nuclear element-1 hypomethylation is a potential biomarker for the prediction of response to oral fluoropyrimidines in microsatellite stable and CpG island methylator phenotype-negative colorectal cancer. Cancer Sci. 2011;102:166–174
9. Deininger PL, Moran JV, Batzer MA, Kazazian HHJ. Mobile elements and mammalian genome evolution. Curr Opin Genet Dev. 2003;6:651–658
10. Phokaew C, Kowudtitham S, Subbalekha K, Shuangshoti S, Mutirangura A. LINE-1 methylation patterns of different loci in normal and cancerous cells. Nucleic Acids Res. 2008;36:5704–5712
11. Di JZ, Han XD, Gu WY, Wang Y, Zheng Q, Zhang P, et al. Association of hypomethylation of LINE-1 repetitive element in blood leukocyte DNA and an increased risk of hepatocellular carcinoma J Zhejiang Univ Sci B. 2011;12:805–811
12. Piyathilake CJ, Macaluso M, Alvarez RD, Chen M, Badiga S, Siddiqui NR, et al. A higher degree of LINE-1 methylation in peripheral blood mononuclear cells, a one-carbon nutrient related epigenetic alteration, is associated with a lower risk of developing cervical intraepithelial neoplasia. Nutrition. 2011;27:513–519
13. Hsiung DT, Marsit CJ, Houseman EA, Eddy K, Furniss CS, McClean MD, et al. Global DNA methylation level in whole blood as a biomarker in head and neck squamous cell carcinoma. Cancer Epidemiol Biomarkers Prev. 2007;16:108–114
14. Mirabello L, Savage SA, Korde L, Gadalla SM, Greene MH. LINE-1 methylation is inherited in familial testicular cancer kindreds. BMC Med Genet. 2010;17:77
15. Liao LM, Brennan P, van Bemmel DM, Zaridze D, Matveev V, Janout V, et al. LINE-1 methylation levels in leukocyte DNA and risk of renal cell cancer. PLoS One. 2011;6:e27361
16. Goldstein AM, Landi MT, Tsang S, Fraser MC, Munroe DJ, Tucker MA. Association of MC1R variants and risk of melanoma in melanoma-prone families with CDKN2A mutations. Cancer Epidemiol Biomarkers Prev. 2005;14:2208–2212
17. Goldstein AM, Struewing JP, Chidambarum A, Fraser MC, Tucker MA. Genotype–phenotype relationships in U.S. melanoma-prone families with CDKN2A and CDK4 mutations. J Natl Cancer Inst. 2000;92:1006–1010
18. Saferali A, Grundberg E, Berlivet S, Beauchemin H, Morcos L, Polychronakos C, et al. Cell culture-induced aberrant methylation of the imprinted IG DMR in human lymphoblastoid cell lines. Epigenetics. 2010;5:50–60
19. Sigalotti L, Fratta E, Bidoli E, Covre A, Parisi G, Colizzi F, et al. Methylation levels of the ‘long interspersed nucleotide element-1’ repetitive sequences predict survival of melanoma patients. J Transl Med. 2011;26:78
20. Liang KY, Zeger SL. Longitudinal data-analysis using generalized linear-models. Biometrika. 1986;73:13–22
21. Xu X, Gammon MD, Hernandez-Vargas H, Herceg Z, Wetmur JG, Teitelbaum SL, et al. DNA methylation in peripheral blood measured by LUMA is associated with breast cancer in a population-based study. FASEB J. 2012;26:2657–2666
22. Zhu ZZ, Hou L, Bollati V, Tarantini L, Marinelli B, Cantone L, et al. Predictors of global methylation levels in blood DNA of healthy subjects: a combined analysis. Int J Epidemiol. 2012;41:126–139
23. Zhang FF, Cardarelli R, Carroll J, Fulda KG, Kaur M, Gonzalez K, et al. Significant differences in global genomic DNA methylation by gender and race/ethnicity in peripheral blood. Epigenetics. 2011;6:623–629
24. Jintaridth P, Mutirangura A. Distinctive patterns of age-dependent hypomethylation in interspersed repetitive sequences. Physiol Genomics. 2010;41:194–200
25. El-Maarri O, Walier M, Behne F, van Üüm J, Singer H, Diaz-Lacava A, et al. Methylation at global LINE-1 repeats in human blood are affected by gender but not by age or natural hormone cycles. PLoS One. 2011;19:e16252
26. Choi JY, James SR, Link PA, McCann SE, Hong CC, Davis W, et al. Association between global DNA hypomethylation in leukocytes and risk of breast cancer. Carcinogenesis. 2009;30:1889–1897
27. Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 2011;12:405

CDKN2A; cutaneous malignant melanoma; DNA methylation; epigenetics; family; LINE-1; melanoma; peripheral blood

© 2013 Lippincott Williams & Wilkins, Inc.