A panel of genes methylated with high frequency in colorectal cancer

Background: The development of colorectal cancer (CRC) is accompanied by extensive epigenetic changes, including frequent regional hypermethylation particularly of gene promoter regions. Specific genes, including SEPT9, VIM1 and TMEFF2 become methylated in a high fraction of cancers and diagnostic assays for detection of cancer-derived methylated DNA sequences in blood and/or fecal samples are being developed. There is considerable potential for the development of new DNA methylation biomarkers or panels to improve the sensitivity and specificity of current cancer detection tests. Methods: Combined epigenomic methods - activation of gene expression in CRC cell lines following DNA demethylating treatment, and two novel methods of genome-wide methylation assessment - were used to identify candidate genes methylated in a high fraction of CRCs. Multiplexed amplicon sequencing of PCR products from bisulfite-treated DNA of matched CRC and non-neoplastic tissue as well as healthy donor peripheral blood was performed using Roche 454 sequencing. Levels of DNA methylation in colorectal tissues and blood were determined by quantitative methylation specific PCR (qMSP). Results: Combined analyses identified 42 candidate genes for evaluation as DNA methylation biomarkers. DNA methylation profiles of 24 of these genes were characterised by multiplexed bisulfite-sequencing in ten matched tumor/normal tissue samples; differential methylation in CRC was confirmed for 23 of these genes. qMSP assays were developed for 32 genes, including 15 of the sequenced genes, and used to quantify methylation in tumor, adenoma and non-neoplastic colorectal tissue and from healthy donor peripheral blood. 24 of the 32 genes were methylated in \u3e50% of neoplastic samples, including 11 genes that were methylated in 80% or more CRCs and a similar fraction of adenomas. Conclusions: This study has characterised a panel of 23 genes that show elevated DNA methylation in \u3e50% of CRC tissue relative to non-neoplastic tissue. Six of these genes (SOX21, SLC6A15, NPY, GRASP, ST8SIA1 and ZSCAN18) show very low methylation in non-neoplastic colorectal tissue and are candidate biomarkers for stool-based assays, while 11 genes (BCAT1, COL4A2, DLX5, FGF5, FOXF1, FOXI2, GRASP, IKZF1, IRF4, SDC2 and SOX21) have very low methylation in peripheral blood DNA and are suitable for further evaluation as blood-based diagnostic markers

Evaluating the association of common APOA2 variants with type 2 diabetes

<p>Abstract</p> <p>Background</p> <p><it>APOA2 </it>is a positional and biological candidate gene for type 2 diabetes at the chromosome 1q21-q24 susceptibility locus. The aim of this study was to examine if HapMap phase II tag SNPs in <it>APOA2 </it>are associated with type 2 diabetes and quantitative traits in French Caucasian subjects.</p> <p>Methods</p> <p>We genotyped the three HapMap phase II tagging SNPs (rs6413453, rs5085 and rs5082) required to capture the common variation spanning the <it>APOA2 </it>locus in our type 2 diabetes case-control cohort comprising 3,093 French Caucasian subjects. The association between these variants and quantitative traits was also examined in the normoglycaemic adults of the control cohort. In addition, meta-analysis of publicly available whole genome association data was performed.</p> <p>Results</p> <p>None of the <it>APOA2 </it>tag SNPs were associated with type 2 diabetes in the French Caucasian case-control cohort (rs6413453, <it>P </it>= 0.619; rs5085, <it>P </it>= 0.245; rs5082, <it>P </it>= 0.591). However, rs5082 was marginally associated with total cholesterol levels (<it>P </it>= 0.026) and waist-to-hip ratio (<it>P </it>= 0.029). The meta-analysis of data from 12,387 subjects confirmed our finding that common variation at the <it>APOA2 </it>locus is not associated with type 2 diabetes.</p> <p>Conclusion</p> <p>The available data does not support a role for common variants in <it>APOA2 </it>on type 2 diabetes susceptibility or related quantitative traits in Northern Europeans.</p

Evaluating the association of common PBX1 variants with type 2 diabetes

<p>Abstract</p> <p>Background</p> <p><it>PBX1 </it>is a biological candidate gene for type 2 diabetes at the 1q21-q24 susceptibility locus. The aim of this study was to evaluate the association of common <it>PBX1 </it>variants with type 2 diabetes in French Caucasian subjects.</p> <p>Methods</p> <p>Employing a case-control design, we genotyped 39 SNPs spanning the <it>PBX1 </it>locus in 3,093 subjects to test for association with type 2 diabetes.</p> <p>Results</p> <p>Several <it>PBX1 </it>SNPs, including the G21S coding SNP rs2275558, were nominally associated with type 2 diabetes but the strongest result was obtained with the intron 2 SNP rs2792248 (P = 0.004, OR 1.20 [95% CI 1.06–1.37]). The SNPSpD multiple testing correction method gave a significance threshold of P = 0.002 for the 39 SNPs genotyped, indicating that the rs2792248 association did not survive multiple testing adjustment. SNP rs2792248 did not show evidence of association with the French 1q linkage signal (P = 0.31; weighted NPL score 2.16). None of the <it>PBX1 </it>SNPs nominally associated with type 2 diabetes were associated with a range of quantitative metabolic traits in the normoglycemic control subjects</p> <p>Conclusion</p> <p>The available data does not support a major influence of common <it>PBX1 </it>variants on type 2 diabetes susceptibility or quantitative metabolic traits. In order to make progress in identifying the elusive susceptibility variants in the 1q region it will be necessary to carry out further large association studies, meta-analyses of existing data from individual studies, and deep resequencing of the 1q region.</p

HV Association results examining the top 10 ranked genetic polymorphisms for late-onset Alzheimer’s Disease in the CHARGE discovery meta-analysis, Sydney MAS, OATS and meta-analyses of MAS/OATS.

<p><b>Notes</b>. Alzgene results from <a href="http://alzgene.org" target="_blank">http://alzgene.org</a>, accessed 10/12/12;</p><p>^aFrom [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116920#pone.0116920.ref010" target="_blank">10</a>];</p><p>^b covariates: age & sex;</p><p>^c<i>APOE ε4</i> carriers vs non-carriers;</p><p>Sydney MAS = Sydney Memory & Ageing Study; OATS = Older Australian Twins Study; n.a.: Not applicable due to poor imputation quality for this SNP; NA: not available;</p><p>* <i>p</i>≤.05;</p><p>** <i>p</i>≤.001</p><p>HV Association results examining the top 10 ranked genetic polymorphisms for late-onset Alzheimer’s Disease in the CHARGE discovery meta-analysis, Sydney MAS, OATS and meta-analyses of MAS/OATS.</p

Replication results of prior genome-wide significant HV SNPs for Sydney MAS and OATS by cohort and meta-analysis.

<p><b><i>Notes</i></b>. MDS = multi-dimensional components; ICV = intracranial volume; Sydney MAS = Sydney Memory & Ageing Study, OATS = Older Australian Twins Study;</p><p>* <i>p</i>-value≤.05</p><p>Replication results of prior genome-wide significant HV SNPs for Sydney MAS and OATS by cohort and meta-analysis.</p

Descriptive statistics for Sydney MAS and OATS participants with hippocampal volume and genotyping data available.

<p><b>Notes</b>. MAS = Sydney Memory & Ageing Study; OATS = Older Australian Twins Study; HV = hippocampal volume;</p><p>^aData presented for those with both HV & genetic data;</p><p>^bData presented for those with Wave 1 & 2 HV & genetic data;</p><p>^c(Wave 2 -Wave1/Wave 1) *100;</p><p>NA = not available</p><p>Descriptive statistics for Sydney MAS and OATS participants with hippocampal volume and genotyping data available.</p

HV association of genetic variants previously identified as having relevance to HV (Stein et al. 2012) in ENIGMA, Sydney MAS, OATS and a meta-analysis of MAS/OATS.

<p><b>Notes</b>. In the ENIGMA analyses, a proxy (in high LD) was used if the named SNP was not available;</p><p>^a From [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116920#pone.0116920.ref001" target="_blank">1</a>];</p><p>^<b>b</b> ENIGMA covariates: age, sex, age², age × sex interaction, age² × sex interaction, 4 multi-dimensional components (MDS), dummy variables for different scanners, ICV (intracranial volume);</p><p>Sydney MAS = Sydney Memory & Ageing Study; OATS = Older Australian Twins Study; n.a.: Not applicable due to poor imputation quality for this SNP; NA: not available;</p><p>* <i>p</i>≤.05</p><p>HV association of genetic variants previously identified as having relevance to HV (Stein et al. 2012) in ENIGMA, Sydney MAS, OATS and a meta-analysis of MAS/OATS.</p