Logistic regression analysis for association with methylation between CRC cases and controls.

<p>Mean β value of CRC cases and controls is shown along with logistic regression analysis at seven CpG sites in the <i>MLH1</i> CpG island shore. Analysis of CRC cases versus controls is adjusted for age and sex. Effect size represents the increased risk of CRC per 1% reduction in methylation.</p

MLH1 Region Polymorphisms Show a Significant Association with CpG Island Shore Methylation in a Large Cohort of Healthy Individuals

<div><p>Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation. We previously demonstrated that SNPs (rs1800734, rs749072, and rs13098279) in the <em>MLH1</em> gene region are associated with <em>MLH1</em> promoter island methylation, loss of MLH1 protein expression, and microsatellite instability (MSI) in colorectal cancer (CRC) patients. Recent studies have identified less CpG-dense “shore” regions flanking many CpG islands. These shores often exhibit distinct methylation profiles between different tissues and matched normal versus tumor cells of patients. To date, most epigenetic studies have focused on <em>somatic</em> methylation events occurring within solid tumors; less is known of the contributions of peripheral blood cell (PBC) methylation to processes such as aging and tumorigenesis. To address whether <em>MLH1</em> methylation in PBCs is correlated with tumorigenesis we utilized the Illumina 450 K microarrays to measure methylation in PBC DNA of 846 healthy controls and 252 CRC patients from Ontario, Canada. Analysis of a region of chromosome 3p21 spanning the <em>MLH1</em> locus in healthy controls revealed that a CpG island shore 1 kb upstream of the <em>MLH1</em> gene exhibits different methylation profiles when stratified by SNP genotypes (rs1800734, rs749072, and rs13098279). Individuals with wild-type genotypes incur significantly higher PBC shore methylation than heterozygous or homozygous variant carriers (p<1.1×10⁻⁶; ANOVA). This trend is also seen in CRC cases (p<0.096; ANOVA). Shore methylation also decreases significantly with increasing age in cases and controls. This is the first study of its kind to integrate PBC methylation at a CpG island shore with SNP genotype status in CRC cases and controls. These results indicate that CpG island shore methylation in PBCs may be influenced by genotype as well as the normal aging process.</p> </div

Correlation between age and methylation.

<p>Partial correlation, controlling for sex, between age and methylation at seven sites in the <i>MLH1</i> CpG island shore for CRC cases and controls. Significant results are bolded when p<0.001.</p

Characteristics of study population.

<p>Distribution of clinicopathological features in primary colorectal carcinomas and controls from Ontario. Age at study recruitment is indicated for CRC cases and controls. Blood was drawn an average of less than one year and no more than six years after study recruitment.</p><p>SD = standard deviation.</p

Locations of CpG sites and methylation between cases and controls.

<p>Pictured are the 70 CpG sites analyzed, with indicated chromosomal positions located on chromosome 3. The CpG sites are located within the <i>EPM2AIP1, MLH1,</i> and <i>LRRFIP2</i> genes, with gene exons and transcriptional directions indicated. CpG islands are indicated in green. The seven CpG sites of the <i>MLH1</i> shore are highlighted in red. Each vertical bar represents a CpG site, with control methylation, n = 846, displayed to the left and CRC case methylation, n = 252, displayed to the right of the white dotted line. Controls and CRC case samples are displayed layered horizontally from highest methylation to lowest methylation. The distribution of degree of methylation in cases and controls is represented by the colour variation, according to the scale.</p

Associations between gender and methylation by logistic regression.

<p>Mean β value of is shown for males and females along with logistic regression analysis at seven CpG sites in the <i>MLH1</i> CpG island shore. Analysis of male versus female methylation is adjusted for age. Significant results are bolded when p<0.001.</p

Methylation between SNP genotypes in CRC cases by ANOVA.

<p>Mean β value of each genotype of the SNPs rs1800734, rs749072, and rs13098279 in CRC patients from Ontario at seven sites in the <i>MLH1</i> CpG island shore. Significant results are bolded when p<0.001.</p

Methylation between SNP genotypes in healthy controls by ANOVA.

<p>Mean β value of each genotype of the SNPs rs1800734, rs749072, and rs13098279 in healthy controls from Ontario at seven sites in the <i>MLH1</i> CpG island shore. Chromosome 3 locations and Probe IDs are the same for CpG sites S1–S7 in subsequent tables. Significant results are bolded when p<0.001.</p>a<p>Probe ID according to Illumina Infinium HumanMethylation450 array, used throughout in tables.</p><p>CI = confidence interval.</p

Single marker analysis in the combined data for 3 SNPs for CRC cases versus controls, <i>MLH1</i> promoter methylation, MLH1 IHC staining and MSI tumor status.

<p>Analyses of CRC cases versus controls are adjusted for age, sex, and site.</p><p>OR  =  odds ratio, CI  =  confidence interval.</p><p>Single marker results for the above SNPs for each study population are shown in <b>Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013314#pone.0013314.s002" target="_blank">File S2</a></b>.</p

Logistic regression model results for MSI status with various predictor combinations in the combined data.

<p>Age at diagnosis, sex, and location are covariates common to all the models described above. IHC refers to the MLH1 immunohistochemical staining variable, CH3 refers to the <i>MLH1</i> promoter methylation variable, AIC  =  Akaike's information criterion. Logistic regression models for each SNP per study population and for the combined data are shown in <b>Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013314#pone.0013314.s003" target="_blank">File S3</a></b>.</p><p>The role of three SNPs of interest, rs1800734, rs749072, and rs13098279, is explored.</p