Epigenome-Wide Association Study of CpG Methylation in Aggressive Behavior

Background. Gestational diabetes mellitus (GDM) is the most prevalent metabolic disease during pregnancy, but the diagnosis is controversial and lagging partly due to the lack of useful biomarkers. CpG methylation is involved in the development of GDM. However, the specific CpG methylation sites serving as diagnostic biomarkers of GDM remain unclear. Here, we aimed to explore CpG signatures and establish the predicting model for the GDM diagnosis. Methods. DNA methylation data of GSE88929 and GSE102177 were obtained from the GEO database, followed by the epigenome-wide association study (EWAS). GO and KEGG pathway analyses were performed by using the clusterProfiler package of R. The PPI network was constructed in the STRING database and Cytoscape software. The SVM model was established, in which the β-values of selected CpG sites were the predictor variable and the occurrence of GDM was the outcome variable. Results. We identified 62 significant CpG methylation sites in the GDM samples compared with the control samples. GO and KEGG analyses based on the 62 CpG sites demonstrated that several essential cellular processes and signaling pathways were enriched in the system. A total of 12 hub genes related to the identified CpG sites were found in the PPI network. The SVM model based on the selected CpGs within the promoter region, including cg00922748, cg05216211, cg05376185, cg06617468, cg17097119, and cg22385669, was established, and the AUC values of the training set and testing set in the model were 0.8138 and 0.7576. The AUC value of the independent validation set of GSE102177 was 0.6667. Conclusion. We identified potential diagnostic CpG signatures by EWAS integrated with the SVM model. The SVM model based on the identified 6 CpG sites reliably predicted the GDM occurrence, contributing to the diagnosis of GDM. Our finding provides new insights into the cross-application of EWAS and machine learning in GDM investigation.

Download Full-text

DDIS-07. IDENTIFICATION OF DRUGGABLE MOLECULAR TARGETS IN MENINGIOMA

Neuro-Oncology ◽

10.1093/neuonc/noz175.267 ◽

2019 ◽

Vol 21 (Supplement_6) ◽

pp. vi66-vi66

Author(s):

Anh Tran ◽

Lyndsee Zhang ◽

Felix Sahm ◽

Denise Scholtens ◽

Craig Horbinski

Keyword(s):

Aggressive Behavior ◽

Signaling Pathways ◽

Progression Free Survival ◽

Cpg Methylation ◽

Published Data ◽

Cpg Sites ◽

Genes Encoding ◽

Prognostic Stratification ◽

Raloxifene Hydrochloride ◽

Primary Intracranial Tumor

Abstract BACKGROUND Meningioma is the most common primary intracranial tumor, with nearly 30,000 new cases in the US every year. Many meningiomas invade the brain, recur, and become radioresistant, causing severe disability and lethality. Prior work by Sahm et al. showed that meningiomas have consistent patterns of global CpG methylation, and that those patterns are better at prognostic stratification than traditional WHO grading (Lancet Oncol. 2017 May;18(5):682–694). In this study, we hypothesized that specific methylation events could provide further insights as to the signaling pathways driving more aggressive behavior, and identify druggable targets. METHODS We analyzed the Illumina 450k CpG methylation profiles of 493 meningiomas that were published in Lancet Oncology, searching for associations between methylation at individual CpG sites and progression-free survival (PFS). Pathway enrichment analyses were performed using gProfiler and Reactome for genes closest to significant CpG sites, followed by screening for candidate drugs targeting the pathways that were linked with malignant behavior using the ReactomeFIViz Cytoscape Plugin. RESULTS Our analyses revealed 981 genes in which methylation of mapped CpG sites was consistently associated with either shorter PFS (positive hazard ratios (HRs)) or longer PFS (negative HRs) at FDR-adjusted p< 0.05. Methylation of genes encoding proteins involved in G-protein coupled receptor (GPCR) signaling pathways, especially G-alpha (s) and olfactory signaling pathways, showed pronounced association with PFS. We identified 134 anticancer drugs that target the GPCR pathway, including docetaxel and raloxifene hydrochloride, which specifically target G alpha (s) subcomponents. Both are FDA-approved, but no published data exist on their use in meningiomas. CONCLUSIONS This project is advancing our understanding of the molecular pathways driving aggressive behavior in meningioma, and is identifying existing drugs that can be repurposed to treat this tumor.

Download Full-text

Epigenome-Wide Association Study of Aggressive Behavior

Twin Research and Human Genetics ◽

10.1017/thg.2015.74 ◽

2015 ◽

Vol 18 (6) ◽

pp. 686-698 ◽

Cited By ~ 23

Author(s):

Jenny van Dongen ◽

Michel G. Nivard ◽

Bart M. L. Baselmans ◽

Nuno R. Zilhão ◽

Lannie Ligthart ◽

...

Keyword(s):

Dna Methylation ◽

Aggressive Behavior ◽

Association Study ◽

Complex Traits ◽

Methylation Level ◽

Self Report ◽

Peripheral Tissues ◽

Association Analyses ◽

Entire Cohort ◽

Discordant Twins

Aggressive behavior is highly heritable, while environmental influences, particularly early in life, are also important. Epigenetic mechanisms, such as DNA methylation, regulate gene expression throughout development and adulthood, and may mediate genetic and environmental effects on complex traits. We performed an epigenome-wide association study (EWAS) to identify regions in the genome where DNA methylation level is associated with aggressive behavior. Subjects took part in longitudinal survey studies from the Netherlands Twin Register (NTR) and participated in the NTR biobank project between 2004 and 2011 (N = 2,029, mean age at blood sampling = 36.4 years, SD = 12.4, females = 69.2%). Aggressive behavior was rated with the ASEBA Adult Self-Report (ASR). DNA methylation was measured in whole blood by the Illumina HM450k array. The association between aggressive behavior and DNA methylation level at 411,169 autosomal sites was tested. Association analyses in the entire cohort showed top sites at cg01792876 (chr8; 116,684,801, nearest gene = TRPS1, p = 7.6 × 10−7, False discovery rate (FDR) = 0.18) and cg06092953 (chr18; 77,905,699, nearest gene = PARD6G-AS1, p = 9.0 ×10−7, FDR = 0.18). Next, we compared methylation levels in 20 pairs of monozygotic (MZ) twins highly discordant for aggression. Here the top sites were cg21557159 (chr 11; 107,795,699, nearest gene = RAB39, p = 5.7 × 10−6, FDR = 0.99), cg08648367 (chr 19; 51,925,472, nearest gene = SIGLEC10, p = 7.6 × 10−6, FDR = 0.99), and cg14212412 (chr 6; 105,918,992, nearest gene = PREP, p = 8.0 × 10−6, FDR = 0.99). The two top hits based on the entire cohort showed the same direction of effect in discordant MZ pairs (cg01792876, Pdiscordant twins = 0.09 and cg06092953, Pdiscordant twins = 0.24). The other way around, two of the three most significant sites in discordant MZ pairs showed the same direction of effect in the entire cohort (cg08648367, Pentire EWAS = 0.59 and cg14212412, Pentire EWAS = 3.1 × 10−3). Gene ontology analysis highlighted significant enrichment of various central nervous system categories among higher-ranking methylation sites. Higher-ranking methylation sites also showed enrichment for DNase I hypersensitive sites and promoter regions, showing that DNA methylation in peripheral tissues is likely to be associated with aggressive behavior.

Download Full-text