DNA methylation and cis-regulation of gene expression by prostate cancer risk SNPs

Genetic effects on the skin methylome in healthy older twins

Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.

CSPG4P12 polymorphism served as a susceptibility marker for esophageal cancer in Chinese population

BACKGROUND

Chondroitin sulfate proteoglycan 4 pseudogene 12 (CSPG4P12) has been implicated in the pathogenesis of various cancers. This study aimed to evaluate the association of the CSPG4P12 polymorphism with esophageal squamous cell carcinoma (ESCA) risk and to explore the biological impact of CSPG4P12 expression on ESCA cell behavior.

METHODS

A case-control study was conducted involving 480 ESCA patients and 480 healthy controls to assess the association between the rs8040855 polymorphism and ESCA risk. The CSPG4P12 rs8040855 genotype was identified using the TaqMan-MGB probe method. Logistic regression model was used to evaluate the association of CSPG4P12 SNP with the risk of ESCA by calculating the odds ratios (OR) and 95% confidence intervals (95%CI ). The effects of CSPG4P12 overexpression on cell proliferation, migration, and invasion were examined in ESCA cell lines. Co-expressed genes were identified via the CBioportal database, with pathway enrichment analyzed using SangerBox. The binding score of CSPG4P12 to P53 was calculated using RNA protein interaction prediction (RPISeq). Additionally, Western Blot analysis was performed to investigate the impact of CSPG4P12 overexpression on the P53/PI3K/AKT signaling pathway.

RESULTS

The presence of at least one rs8040855 G allele was associated with a reduced susceptibility to ESCA compared to the CC genotype (OR = 0.51, 95%CI = 0.28-0.93, P = 0.03). Stratification analysis revealed that the CSPG4P12 rs8040855 C allele significantly decreased the risk of ESCA among younger individuals (≤ 57 years) and non-drinkers (OR = 0.31, 95%CI = 0.12-0.77, P = 0.01; OR = 0.42, 95%CI=0.20-0.87, P = 0.02, respectively). CSPG4P12 expression was found to be downregulated in ESCA tissues compared to adjacent normal tissues. Overexpression of CSPG4P12 in ESCA cells inhibited their proliferation, migration, and invasion capabilities. Furthermore, Western Blot analysis indicated that CSPG4P12 overexpression led to a reduction in PI3K and p-AKT protein expression levels. P53 silencing rescues the inhibitory effect of CSPG4P12 on p-AKT.

CONCLUSION

The CSPG4P12 rs8040855 variant is associated with reduced ESCA risk and the overexpression of CSPG4P12 inhibited the migration and invasion of ESCA cells by P53/PI3K/AKT pathway. These findings suggest that CSPG4P12 may serve as a novel biomarker for ESCA susceptibility and a potential target for therapeutic intervention.

The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men

BACKGROUND

American men of African ancestry (AA) have higher prostate cancer incidence and mortality rates compared with American men of European ancestry (EA). Differences in genetic susceptibility mechanisms may contribute to this disparity.

METHODS

To gain insights into the regulatory mechanisms of prostate cancer susceptibility variants, we tested the association between SNPs and DNA methylation (DNAm) at nearby CpG sites across the genome in benign and cancer prostate tissue from 74 AA and 74 EA men. Genome-wide SNP data (from benign tissue) and DNAm were generated using Illumina arrays.

RESULTS

Among AA men, we identified 6,298 and 2,641 cis-methylation QTLs (meQTL; FDR of 0.05) in benign and tumor tissue, respectively, with 6,960 and 1,700 detected in EA men. We leveraged genome-wide association study (GWAS) summary statistics to identify previously reported prostate cancer GWAS signals likely to share a common causal variant with a detected meQTL. We identified nine GWAS-meQTL pairs with strong evidence of colocalization (four in EA benign, three in EA tumor, two in AA benign, and three in AA tumor). Among these colocalized GWAS-meQTL pairs, we identified colocalizing expression quantitative trait loci (eQTL) impacting four eGenes with known roles in tumorigenesis.

CONCLUSIONS

These findings highlight epigenetic regulatory mechanisms by which prostate cancer-risk SNPs can modify local DNAm and/or gene expression in prostate tissue.

IMPACT

Overall, our findings showed general consistency in the meQTL landscape of AA and EA men, but meQTLs often differ by tissue type (normal vs. cancer). Ancestry-based linkage disequilibrium differences and lack of AA representation in GWAS decrease statistical power to detect colocalization for some regions.

Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma

BACKGROUND

Aberrations in MYC underlie a large proportion of liver hepatocellular carcinoma (LIHC) cases; however, MYC is difficult to target because of its undruggable structure. We aimed to uncover MYC-associated molecular targets to provide new strategies for LIHC treatment.

METHODS

LIHC transcriptome datasets and clinical information were obtained from The Cancer Genome Atlas. A series of bioinformatics analyses were performed for 370 patients who were stratified based on the median MYC expression level (high-MYC group and low-MYC group). Correlation analysis was performed to determine relationships between the expression of key MYC-associated genes and prognosis, DNA promotor methylation, and immune cell infiltration. Gene ontology and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analyses were performed to elucidate the functions of these genes in LIHC. Their expression and functions in LIHC were further verified using transgenic mice overexpressing c-Myc under control of the hepatocyte-specific promoter (Alb-Cre).

RESULTS

AURKB, CCNB2, and CDKN3 were overexpressed in LIHC patients with high MYC expression and were associated with poor prognosis. Upregulation of these 3 genes was significantly correlated with hypomethylated promoter status, advanced T stage, metastasis, and immune cell infiltration in LIHC patients. Functional enrichment analyses indicated that these genes participate in the "p53 signaling pathway" and "cell cycle". Furthermore, RT-PCR and IHC analysis revealed that their mRNA and protein expression levels were upregulated in an Alb-Cre;cMYClsl/- mouse model. Drugs that target these 3 MYC-related genes were identified.

CONCLUSION

Taken together, our results identify biomarkers of potential utility for managing liver cancer therapy owing to their significance in tumorigenesis, proliferation, and tumor immunity.

Polymorphic variants involved in methylation regulation: a strategy to discover risk loci for pancreatic ductal adenocarcinoma

INTRODUCTION

Only a small number of risk factors for pancreatic ductal adenocarcinoma (PDAC) has been established. Several studies identified a role of epigenetics and of deregulation of DNA methylation. DNA methylation is variable across a lifetime and in different tissues; nevertheless, its levels can be regulated by genetic variants like methylation quantitative trait loci (mQTLs), which can be used as a surrogate.

MATERIALS AND METHODS

We scanned the whole genome for mQTLs and performed an association study in 14 705 PDAC cases and 246 921 controls. The methylation data were obtained from whole blood and pancreatic cancer tissue through online databases. We used the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium genome-wide association study (GWAS) data as discovery phase and the Pancreatic Disease Research consortium, the FinnGen project and the Japan Pancreatic Cancer Research consortium GWAS as replication phase.

RESULTS

The C allele of 15q26.1-rs12905855 showed an association with a decreased risk of PDAC (OR=0.90, 95% CI 0.87 to 0.94, p=4.93×10-8 in the overall meta-analysis), reaching genome-level statistical significance. 15q26.1-rs12905855 decreases the methylation of a 'C-phosphate-G' (CpG) site located in the promoter region of the RCCD1 antisense (RCCD1-AS1) gene which, when expressed, decreases the expression of the RCC1 domain-containing (RCCD1) gene (part of a histone demethylase complex). Thus, it is possible that the rs12905855 C-allele has a protective role in PDAC development through an increase of RCCD1 gene expression, made possible by the inactivity of RCCD1-AS1.

CONCLUSION

We identified a novel PDAC risk locus which modulates cancer risk by controlling gene expression through DNA methylation.

LARP4A and LARP4B in cancer: The new kids on the block

Recent developments have mounted a stunning body of evidence underlying the importance of RNA binding proteins (RBPs) in cancer research. In this minireview we focus on LARP4A and LARP4B, two paralogs belonging to the superfamily of La-related proteins, and provide a critical overview of current research, including their roles in cancer pathogenesis and cell proliferation, migration, cell cycle and apoptosis. We highlight current controversies surrounding LARP4A and LARP4B and conclude that their complex roles in tumorigenesis are cell-, tissue- and context-dependent, warning that caution must be exercised before categorising either protein as an oncoprotein or tumour-suppressor. We also reveal that LARP4A and LARP4B have often been confused with one another, adding uncertainty in delineating their functions. We suggest that further functional and mechanistic studies of LARP4 proteins present significant challenges for future investigations to recognise the vital contributions of these RBPs in cancer research.

meQTL mapping in the GENOA study reveals genetic determinants of DNA methylation in African Americans

Identifying genetic variants that are associated with variation in DNA methylation, an analysis commonly referred to as methylation quantitative trait locus (meQTL) mapping, is an important first step towards understanding the genetic architecture underlying epigenetic variation. Most existing meQTL mapping studies have focused on individuals of European ancestry and are underrepresented in other populations, with a particular absence of large studies in populations with African ancestry. We fill this critical knowledge gap by performing a large-scale cis-meQTL mapping study in 961 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We identify a total of 4,565,687 cis-acting meQTLs in 320,965 meCpGs. We find that 45% of meCpGs harbor multiple independent meQTLs, suggesting potential polygenic genetic architecture underlying methylation variation. A large percentage of the cis-meQTLs also colocalize with cis-expression QTLs (eQTLs) in the same population. Importantly, the identified cis-meQTLs explain a substantial proportion (median = 24.6%) of methylation variation. In addition, the cis-meQTL associated CpG sites mediate a substantial proportion (median = 24.9%) of SNP effects underlying gene expression. Overall, our results represent an important step toward revealing the co-regulation of methylation and gene expression, facilitating the functional interpretation of epigenetic and gene regulation underlying common diseases in African Americans.

Investigating DNA methylation as a mediator of genetic risk in childhood acute lymphoblastic leukemia

Genome-wide association studies have identified a growing number of single nucleotide polymorphisms (SNPs) associated with childhood acute lymphoblastic leukemia (ALL), yet the functional roles of most SNPs are unclear. Multiple lines of evidence suggest that epigenetic mechanisms may mediate the impact of heritable genetic variation on phenotypes. Here, we investigated whether DNA methylation mediates the effect of genetic risk loci for childhood ALL. We performed an epigenome-wide association study (EWAS) including 808 childhood ALL cases and 919 controls from California-based studies using neonatal blood DNA. For differentially methylated CpG positions (DMPs), we next conducted association analysis with 23 known ALL risk SNPs followed by causal mediation analyses addressing the significant SNP-DMP pairs. DNA methylation at CpG cg01139861, in the promoter region of IKZF1, mediated the effects of the intronic IKZF1 risk SNP rs78396808, with the average causal mediation effect (ACME) explaining ~30% of the total effect (ACME P = 0.0031). In analyses stratified by self-reported race/ethnicity, the mediation effect was only significant in Latinos, explaining ~41% of the total effect of rs78396808 on ALL risk (ACME P = 0.0037). Conditional analyses confirmed the presence of at least three independent genetic risk loci for childhood ALL at IKZF1, with rs78396808 unique to non-European populations. We also demonstrated that the most significant DMP in the EWAS, CpG cg13344587 at gene ARID5B (P = 8.61 × 10-10), was entirely confounded by the ARID5B ALL risk SNP rs7090445. Our findings provide new insights into the functional pathways of ALL risk SNPs and the DNA methylation differences associated with risk of childhood ALL.

Simultaneous test and estimation of total genetic effect in eQTL integrative analysis through mixed models

Integration of expression quantitative trait loci (eQTL) into genome-wide association studies (GWASs) is a promising manner to reveal functional roles of associated single-nucleotide polymorphisms (SNPs) in complex phenotypes and has become an active research field in post-GWAS era. However, how to efficiently incorporate eQTL mapping study into GWAS for prioritization of causal genes remains elusive. We herein proposed a novel method termed as Mixed transcriptome-wide association studies (TWAS) and mediated Variance estimation (MTV) by modeling the effects of cis-SNPs of a gene as a function of eQTL. MTV formulates the integrative method and TWAS within a unified framework via mixed models and therefore includes many prior methods/tests as special cases. We further justified MTV from another two statistical perspectives of mediation analysis and two-stage Mendelian randomization. Relative to existing methods, MTV is superior for pronounced features including the processing of direct effects of cis-SNPs on phenotypes, the powerful likelihood ratio test for assessment of joint effects of cis-SNPs and genetically regulated gene expression (GReX), two useful quantities to measure relative genetic contributions of GReX and cis-SNPs to phenotypic variance, and the computationally efferent parameter expansion expectation maximum algorithm. With extensive simulations, we identified that MTV correctly controlled the type I error in joint evaluation of the total genetic effect and proved more powerful to discover true association signals across various scenarios compared to existing methods. We finally applied MTV to 41 complex traits/diseases available from three GWASs and discovered many new associated genes that had otherwise been missed by existing methods. We also revealed that a small but substantial fraction of phenotypic variation was mediated by GReX. Overall, MTV constructs a robust and realistic modeling foundation for integrative omics analysis and has the advantage of offering more attractive biological interpretations of GWAS results.

Novel prostate cancer susceptibility gene SP6 predisposes patients to aggressive disease

Prostate cancer (PrCa) is one of the most common cancers in men, but little is known about factors affecting its clinical outcomes. Genome-wide association studies have identified more than 170 germline susceptibility loci, but most of them are not associated with aggressive disease. We performed a genome-wide analysis of 185,478 SNPs in Finnish samples (2738 cases, 2400 controls) from the international Collaborative Oncological Gene-Environment Study (iCOGS) to find underlying PrCa risk variants. We identified a total of 21 common, low-penetrance susceptibility loci, including 10 novel variants independently associated with PrCa risk. Novel risk loci were located in the 8q24 (CASC8 rs16902147, OR 1.86, padj = 3.53 × 10-8 and rs58809953, OR 1.71, padj = 4.00 × 10-6; intergenic rs79012498, OR 1.81, padj = 4.26 × 10-8), 17q21 (SP6 rs2074187, OR 1.66, padj = 3.75 × 10-5), 11q13 (rs12795301, OR 1.42, padj = 2.89 × 10-5) and 8p21 (rs995432, OR 1.38, padj = 3.00 × 10-11) regions. Here, we describe SP6, a transcription factor gene, as a new, potentially high-risk gene for PrCa. The intronic variant rs2074187 in SP6 was associated not only with overall susceptibility to PrCa (OR 1.66) but also with a higher odds ratio for aggressive PrCa (OR 1.89) and lower odds for non-aggressive PrCa (OR 1.43). Furthermore, the new intergenic variant rs79012498 at 8q24 conferred risk for aggressive PrCa. Our findings highlighted the power of a population-stratified approach to identify novel, clinically actionable germline PrCa risk loci and strongly suggested SP6 as a new PrCa candidate gene that may be involved in the pathogenesis of PrCa.

Identification of tissue-specific and common methylation quantitative trait loci in healthy individuals using MAGAR

Background

Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease. There is a need for systematic approaches not only for determining methylation quantitative trait loci (methQTL), but also for discriminating general from cell type-specific effects.

Results

Here, we present a two-step computational framework MAGAR (https://bioconductor.org/packages/MAGAR), which fully supports the identification of methQTLs from matched genotyping and DNA methylation data, and additionally allows for illuminating cell type-specific methQTL effects. In a pilot analysis, we apply MAGAR on data in four tissues (ileum, rectum, T cells, B cells) from healthy individuals and demonstrate the discrimination of common from cell type-specific methQTLs. We experimentally validate both types of methQTLs in an independent data set comprising additional cell types and tissues. Finally, we validate selected methQTLs located in the PON1, ZNF155, and NRG2 genes by ultra-deep local sequencing. In line with previous reports, we find cell type-specific methQTLs to be preferentially located in enhancer elements.

Conclusions

Our analysis demonstrates that a systematic analysis of methQTLs provides important new insights on the influences of genetic variants to cell type-specific epigenomic variation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-021-00415-6.

Cell-type-specific meQTLs extend melanoma GWAS annotation beyond eQTLs and inform melanocyte gene-regulatory mechanisms

Although expression quantitative trait loci (eQTLs) have been powerful in identifying susceptibility genes from genome-wide association study (GWAS) findings, most trait-associated loci are not explained by eQTLs alone. Alternative QTLs, including DNA methylation QTLs (meQTLs), are emerging, but cell-type-specific meQTLs using cells of disease origin have been lacking. Here, we established an meQTL dataset by using primary melanocytes from 106 individuals and identified 1,497,502 significant cis-meQTLs. Multi-QTL colocalization with meQTLs, eQTLs, and mRNA splice-junction QTLs from the same individuals together with imputed methylome-wide and transcriptome-wide association studies identified candidate susceptibility genes at 63% of melanoma GWAS loci. Among the three molecular QTLs, meQTLs were the single largest contributor. To compare melanocyte meQTLs with those from malignant melanomas, we performed meQTL analysis on skin cutaneous melanomas from The Cancer Genome Atlas (n = 444). A substantial proportion of meQTL probes (45.9%) in primary melanocytes is preserved in melanomas, while a smaller fraction of eQTL genes is preserved (12.7%). Integration of melanocyte multi-QTLs and melanoma meQTLs identified candidate susceptibility genes at 72% of melanoma GWAS loci. Beyond GWAS annotation, meQTL-eQTL colocalization in melanocytes suggested that 841 unique genes potentially share a causal variant with a nearby methylation probe in melanocytes. Finally, melanocyte trans-meQTLs identified a hotspot for rs12203592, a cis-eQTL of a transcription factor, IRF4, with 131 candidate target CpGs. Motif enrichment and IRF4 ChIP-seq analysis demonstrated that these target CpGs are enriched in IRF4 binding sites, suggesting an IRF4-mediated regulatory network. Our study highlights the utility of cell-type-specific meQTLs.

Associations between pancreatic expression quantitative traits and risk of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancers. Its poor prognosis is predominantly due to the fact that most patients remain asymptomatic until the disease reaches an advanced stage, alongside the lack of early markers and screening strategies. A better understanding of PDAC risk factors is essential for the identification of groups at high risk in the population. Genome-wide association studies (GWAS) have been a powerful tool for detecting genetic variants associated with complex traits, including pancreatic cancer. By exploiting functional and GWAS data, we investigated the associations between polymorphisms affecting gene function in the pancreas (expression quantitative trait loci, eQTLs) and PDAC risk. In a two-phase approach, we analysed 13 713 PDAC cases and 43 784 controls and identified a genome-wide significant association between the A allele of the rs2035875 polymorphism and increased PDAC risk (P = 7.14 × 10-10). This allele is known to be associated with increased expression in the pancreas of the keratin genes KRT8 and KRT18, whose increased levels have been reported to correlate with various tumour cell characteristics. Additionally, the A allele of the rs789744 variant was associated with decreased risk of developing PDAC (P = 3.56 × 10-6). This single nucleotide polymorphism is situated in the SRGAP1 gene and the A allele is associated with higher expression of the gene, which in turn inactivates the cyclin-dependent protein 42 (CDC42) gene expression, thus decreasing the risk of PDAC. In conclusion, we present here a functional-based novel PDAC risk locus and an additional strong candidate supported by significant associations and plausible biological mechanisms.

DNA methylation as a mediator of associations between the environment and chronic diseases: A scoping review on application of mediation analysis

DNA methylation (DNAm) is one of the most studied epigenetic modifications. DNAm has emerged as a key biological mechanism and biomarkers to test associations between environmental exposure and outcomes in epidemiological studies. Although previous studies have focused on associations between DNAm and either exposure/outcomes, it is useful to test for mediation of the association between exposure and outcome by DNAm. The purpose of this scoping review is to introduce the methodological essence of statistical mediation analysis and to examine emerging epidemiological research applying mediation analyses. We conducted this scoping review for published peer-reviewed journals on this topic using online databases (PubMed, Scopus, Cochrane, and CINAHL) ending in December 2020. We extracted a total of 219 articles by initial screening. After reviewing titles, abstracts, and full texts, a total of 69 articles were eligible for this review. The breakdown of studies assigned to each category was 13 for smoking (18.8%), 8 for dietary intake and famine (11.6%), 6 for other lifestyle factors (8.7%), 8 for clinical endpoints (11.6%), 22 for environmental chemical exposures (31.9%), 2 for socioeconomic status (SES) (2.9%), and 10 for genetic factors and race (14.5%). In this review, we provide an exposure-wide summary for the mediation analysis using DNAm levels. However, we found heterogenous methods and interpretations in mediation analysis with typical issues such as different cell compositions and tissue-specificity. Further accumulation of evidence with diverse exposures, populations and with rigorous methodology will be expected to provide further insight in the role of DNAm in disease susceptibility.

RNAAgeCalc: A multi-tissue transcriptional age calculator

Biological aging reflects decline in physiological functions and is an effective indicator of morbidity and mortality. Numerous epigenetic age calculators are available, however biological aging calculators based on transcription remain scarce. Here, we introduce RNAAgeCalc, a versatile across-tissue and tissue-specific transcriptional age calculator. By performing a meta-analysis of transcriptional age signature across multi-tissues using the GTEx database, we identify 1,616 common age-related genes, as well as tissue-specific age-related genes. Based on these genes, we develop new across-tissue and tissue-specific age predictors. We show that our transcriptional age calculator outperforms other prior age related gene signatures as indicated by the higher correlation with chronological age as well as lower median and median error. Our results also indicate that both racial and tissue differences are associated with transcriptional age. Furthermore, we demonstrate that the transcriptional age acceleration computed from our within-tissue predictor is significantly correlated with mutation burden, mortality risk and cancer stage in several types of cancer from the TCGA database, and offers complementary information to DNA methylation age. RNAAgeCalc is available at http://www.ams.sunysb.edu/~pfkuan/softwares.html#RNAAgeCalc, both as Bioconductor and Python packages, accompanied by a user-friendly interactive Shiny app.