Zongli Xu

SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies

We have developed a set of web-based SNP selection tools (freely available at http://www.niehs.nih.gov/snpinfo) where investigators can specify genes or linkage regions and select SNPs based on GWAS results, linkage disequilibrium (LD), and predicted functional characteristics of both coding and non-coding SNPs. The algorithm uses GWAS SNP P-value data and finds all SNPs in high LD with GWAS SNPs, so that selection is from a much larger set of SNPs than the GWAS itself. The program can also identify and choose tag SNPs for SNPs not in high LD with any GWAS SNP. We incorporate functional predictions of protein structure, gene regulation, splicing and miRNA binding, and consider whether the alternative alleles of a SNP are likely to have differential effects on function. Users can assign weights for different functional categories of SNPs to further tailor SNP selection. The program accounts for LD structure of different populations so that a GWAS study from one ethnic group can be used to choose SNPs for one or more other ethnic groups. Finally, we provide an example using prostate cancer and demonstrate that this algorithm can select a small panel of SNPs that include many of the recently validated prostate cancer SNPs.

Identification of DNA Methylation Changes in Newborns Related to Maternal Smoking during Pregnancy

Background: Maternal smoking during pregnancy is associated with significant infant morbidity and mortality, and may influence later disease risk. One mechanism by which smoking (and other environmental factors) might have long-lasting effects is through epigenetic modifications such as DNA methylation. Objectives: We conducted an epigenome-wide association study (EWAS) investigating alterations in DNA methylation in infants exposed in utero to maternal tobacco smoke, using the Norway Facial Clefts Study. Methods: The Illumina HumanMethylation450 BeadChip was used to assess DNA methylation in whole blood from 889 infants shortly after delivery. Of 889 mothers, 287 reported smoking—twice as many smokers as in any previous EWAS of maternal smoking. CpG sites related to maternal smoking during the first trimester were identified using robust linear regression. Results: We identified 185 CpGs with altered methylation in infants of smokers at genome-wide significance (q-value < 0.05; mean Δβ = ± 2%). These correspond to 110 gene regions, of which 7 have been previously reported and 10 are newly confirmed using publicly available results. Among these 10, the most noteworthy are FRMD4A, ATP9A, GALNT2, and MEG3, implicated in processes related to nicotine dependence, smoking cessation, and placental and embryonic development. Conclusions: Our study identified 10 genes with newly established links to maternal smoking. Further, we note differences between smoking-related methylation changes in newborns and adults, suggesting possible distinct effects of direct versus indirect tobacco smoke exposure as well as potential differences due to age. Further work would be needed to determine whether these small changes in DNA methylation are biologically or clinically relevant. The methylation changes identified in newborns may mediate the association between in utero maternal smoking exposure and later health outcomes. Citation: Markunas CA, Xu Z, Harlid S, Wade PA, Lie RT, Taylor JA, Wilcox AJ. 2014. Identification of DNA methylation changes in newborns related to maternal smoking during pregnancy. Environ Health Perspect 122:1147–1153; http://dx.doi.org/10.1289/ehp.1307892

Epigenome-wide Association Study of Breast Cancer Using Prospectively Collected Sister Study Samples

BACKGROUND Previous studies have suggested DNA methylation in blood is a potential epigenetic marker of cancer risk, but this has not been evaluated on a genome-wide scale in prospective studies for breast cancer. METHODS We measured DNA methylation at 27578 CpGs in blood samples from 298 women who developed breast cancer 0 to 5 years after enrollment in the Sister Study cohort and compared them with a random sample of 612 cohort women who remained cancer free. We also genotyped women for nine common polymorphisms associated with breast cancer. RESULTS We identified 250 differentially methylated CpGs (dmCpGs) between case subjects and noncase subjects (false discovery rate [FDR] Q < 0.05). Of these dmCpGs, 75.2% were undermethylated in case subjects relative to noncase subjects. Women diagnosed within 1 year of blood draw had small but consistently greater divergence from noncase subjects than did women diagnosed at more than 1 year. Gene set enrichment analysis identified Kyoto Encyclopedia of Genes and Genomes cancer pathways at the recommended FDR of Q less than 0.25. Receiver operating characteristic analysis estimated a prediction accuracy of 65.8% (95% confidence interval = 61.0% to 70.5%) for methylation, compared with 56.0% for the Gail model and 58.8% for genome-wide association study polymorphisms. The prediction accuracy of just five dmCpGs (64.1%) was almost as good as the larger panel and was similar (63.1%) when replicated in a small sample of 81 women with diverse ethnic backgrounds. CONCLUSIONS Methylation profiling of blood holds promise for breast cancer detection and risk prediction.

Serum microRNA expression as an early marker for breast cancer risk in prospectively collected samples from the Sister Study cohort

IntroductionMicroRNAs (miRNAs) are small, non-coding, single-stranded RNAs between 18-22 nucleotides long that regulate gene expression. Expression of miRNAs is altered in tumor compared to normal tissue; there is some evidence that these changes may be reflected in the serum of cancer cases compared to healthy individuals. This has yet to be examined in a prospective study where samples are collected before diagnosis.MethodsWe used Affymetrix arrays to examine serum miRNA expression profiles in 410 participants in the Sister Study, a prospective cohort study of 50,884 women. All women in the cohort had never been diagnosed with breast cancer at the time of enrollment. We compared global miRNA expression patterns in 205 women who subsequently developed breast cancer and 205 women who remained breast cancer-free. In addition within the case group we examined the association of miRNA expression in serum with different tumor characteristics, including hormone status (ER, PR, and HER-2) and lymph node status.ResultsOverall, 414 of 1,105 of the human miRNAs on the chip were expressed above background levels in 50 or more women. When the average expression among controls was compared to cases using conditional logistic regression, 21 miRNAs were found to be differentially expressed (P≤.05). Using qRT-PCR on a small, independent sample of 5 cases and 5 controls we verified overexpression of the 3 highest expressing miRNAs among cases, miR-18a, miR-181a, and miR-222; the differences were not statistically significant in this small set. The 21 differentially expressed miRNAs are known to target at least 82 genes; using the gene list for pathway analysis we found enrichment of genes involved in cancer-related processes. In a separate case-case analyses restricted to the 21 miRNAs, we found 7 miRNAs with differential expression for women whose breast tumors differed by HER-2 expression, and 10 miRNAs with differential expression by nodal status.ConclusionsmiRNA levels in serum show a number of small differences between women who later develop cancer versus those who remain cancer-free.

CpG sites associated with cigarette smoking: analysis of epigenome-wide data from the Sister Study.

Background: Smoking increases the risk of many diseases, and it is also linked to blood DNA methylation changes that may be important in disease etiology. Objectives: We sought to identify novel CpG sites associated with cigarette smoking. Methods: We used two epigenome-wide data sets from the Sister Study to identify and confirm CpG sites associated with smoking. One included 908 women with methylation measurements at 27,578 CpG sites using the HumanMethylation27 BeadChip; the other included 200 women with methylation measurements for 473,844 CpG sites using the HumanMethylation450 BeadChip. Significant CpGs from the second data set that were not included in the 27K assay were validated by pyrosequencing in a subset of 476 samples from the first data set. Results: Our study successfully confirmed smoking associations for 9 previously established CpGs and identified 2 potentially novel CpGs: cg26764244 in GNG12 (p = 9.0 × 10–10) and cg22335340 in PTPN6 (p = 2.9 × 10–05). We also found strong evidence of an association between smoking status and cg02657160 in CPOX (p = 7.3 × 10–7), which has not been previously reported. All 12 CpGs were undermethylated in current smokers and showed an increasing percentage of methylation in former and never-smokers. Conclusions: We identified 2 potentially novel smoking related CpG sites, and provided independent replication of 10 previously reported CpGs sites related to smoking, one of which is situated in the gene CPOX. The corresponding enzyme is involved in heme biosynthesis, and smoking is known to increase heme production. Our study extends the evidence base for smoking-related changes in DNA methylation. Citation: Harlid S, Xu Z, Panduri V, Sandler DP, Taylor JA. 2014. CpG sites associated with cigarette smoking: analysis of epigenome-wide data from the Sister Study. Environ Health Perspect 122:673–678; http://dx.doi.org/10.1289/ehp.1307480

Recreational and household physical activity at different time points and DNA global methylation

BACKGROUND DNA methylation patterns are heritable but can change over time and in response to exposures. Lower global DNA methylation, which may result in increased genomic and chromosomal instability, has been associated with increased cancer risk. Physical activity is a modifiable factor that has been inversely related to the risk of cancer. Changes in DNA methylation may be a mechanism by which lifestyle and environment factors influence disease. We investigated the relationship between DNA methylation and physical activity in a sample of women enroled in The Sister Study, a large United States (U.S.) cohort study of women aged 35-74 years with a family history of breast cancer. METHODS Global DNA methylation was measured using bisulphite-converted DNA and pyrosequencing of a LINE-1 repetitive sequence in the peripheral blood of 647 non-Hispanic white women. Physical activity (average hours per week) was retrospectively assessed for three time periods: childhood (ages 5-12), teenage years (ages 13-19) and the previous 12 months. FINDINGS Compared with women with physical activity levels below the median for all three time periods, those at or above the median physical activity for one (β = 0.20, 95% confidence interval (CI): -0.10, 0.49), two (β = 0.22, 95% CI: -0.08, 0.52) or all three (β = 0.33, 95% CI: 0.01, 0.66) time periods had increased global methylation. INTERPRETATION Maintaining higher levels of physical activity over these three time periods was associated with increased global DNA methylation, consistent with reported associations between exercise and decreased cancer risk.

Genetic polymorphism and prostate cancer aggressiveness: A case-only study of 1,536 GWAS and candidate SNPs in African-Americans and European-Americans

Genome‐wide association studies have established a number of replicated single nucleotide polymorphisms (SNPs) for susceptibility to prostate cancer (CaP), but it is unclear whether these susceptibility SNPs are also associated with disease aggressiveness. This study evaluates whether such replication SNPs or other candidate SNPs are associated with CaP aggressiveness in African‐American (AA) and European‐American (EA) men.

Global DNA methylation and one-carbon metabolism gene polymorphisms and the risk of breast cancer in the Sister Study.

Global decrease in DNA methylation is a common feature of cancer and is associated with genomic and chromosomal instability. Retrospective case-control studies have reported that cancer patients have lower global methylation levels in blood DNA than do controls. We used prospectively collected samples and a case-cohort study design to examine global DNA methylation and incident breast cancer in 294 cases and a sample of 646 non-cases in the Sister Study, a study of 50 884 women aged 35-74 years who had not been diagnosed with breast cancer at the time of blood draw. Global methylation in DNA from peripheral blood was assessed by pyrosequencing of the LINE-1 repetitive element. Quartiles of LINE-1 methylation levels were associated with the risk of breast cancer in a dose-dependent fashion (P, trend = 0.002), with an increased risk observed among women in the lowest quartile compared with those in the highest quartile (hazard ratio = 1.75; 95% confidence interval 1.19, 2.59). We also examined 22 polymorphisms in 10 one-carbon metabolism genes in relation to both LINE-1 methylation levels and breast cancer. We found three single-nucleotide polymorphisms in those genes associated with LINE-1 methylation: SLC19A1 (rs1051266); MTRR (rs10380) and MTHFR (rs1537514), one of which was also associated with breast cancer risk: MTHFR (rs1537514). PON1 (rs757158) was associated with breast cancer but not methylation.

Tag SNP selection for candidate gene association studies using HapMap and gene resequencing data

HapMap provides linkage disequilibrium (LD) information on a sample of 3.7 million SNPs that can be used for tag SNP selection in whole-genome association studies. HapMap can also be used for tag SNP selection in candidate genes, although its performance has yet to be evaluated against gene resequencing data, where there is near-complete SNP ascertainment. The Environmental Genome Project (EGP) is the largest gene resequencing effort to date with over 500 resequenced genes. We used HapMap data to select tag SNPs and calculated the proportions of common SNPs (MAF≥0.05) tagged (ρ2≥0.8) for each of 127 EGP Panel 2 genes where individual ethnic information was available. Median gene-tagging proportions are 50, 80 and 74% for African, Asian, and European groups, respectively. These low gene-tagging proportions may be problematic for some candidate gene studies. In addition, although HapMap targeted nonsynonymous SNPs (nsSNPs), we estimate only ∼30% of nonsynonymous SNPs in EGP are in high LD with any HapMap SNP. We show that gene-tagging proportions can be improved by adding a relatively small number of tag SNPs that were selected based on resequencing data. We also demonstrate that ethnic-mixed data can be used to improve HapMap gene-tagging proportions, but are not as efficient as ethnic-specific data. Finally, we generalized the greedy algorithm proposed by Carlson et al (2004) to select tag SNPs for multiple populations and implemented the algorithm into a freely available software package mPopTag.

TAGster: efficient selection of LD tag SNPs in single or multiple populations

UNLABELLED Genetic association studies increasingly rely on the use of linkage disequilibrium (LD) tag SNPs to reduce genotyping costs. We developed a software package TAGster to select, evaluate and visualize LD tag SNPs both for single and multiple populations. We implement several strategies to improve the efficiency of current LD tag SNP selection algorithms: (1) we modify the tag SNP selection procedure of Carlson et al. to improve selection efficiency and further generalize it to multiple populations. (2) We propose a redundant SNP elimination step to speed up the exhaustive tag SNP search algorithm proposed by Qin et al. (3) We present an additional multiple population tag SNP selection algorithm based on the framework of Howie et al., but using our modified exhaustive search procedure. We evaluate these methods using resequenced candidate gene data from the Environmental Genome Project and show improvements in both computational and tagging efficiency. AVAILABILITY The software Package TAGster is freely available at http://www.niehs.nih.gov/research/resources/software/tagster/