ABSTRACT
Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks informed by prior biological knowledge, referred to as visible networks. These neural networks offer insights into the decision-making process and can unveil novel perspectives on the underlying biological mechanisms associated with traits and complex diseases. We tested the performance, interpretability and generalizability for inferring smoking status, subject age and LDL levels using genome-wide RNA expression and CpG methylation data from the blood of the BIOS consortium (four population cohorts, Ntotal = 2940). In a cohort-wise cross-validation setting, the consistency of the diagnostic performance and interpretation was assessed. Performance was consistently high for predicting smoking status with an overall mean AUC of 0.95 (95% CI: 0.90-1.00) and interpretation revealed the involvement of well-replicated genes such as AHRR, GPR15 and LRRN3. LDL-level predictions were only generalized in a single cohort with an R2 of 0.07 (95% CI: 0.05-0.08). Age was inferred with a mean error of 5.16 (95% CI: 3.97-6.35) years with the genes COL11A2, AFAP1, OTUD7A, PTPRN2, ADARB2 and CD34 consistently predictive. For both regression tasks, we found that using multi-omics networks improved performance, stability and generalizability compared to interpretable single omic networks. We believe that visible neural networks have great potential for multi-omics analysis; they combine multi-omic data elegantly, are interpretable, and generalize well to data from different cohorts.
Subject(s)
Neural Networks, Computer , Phenotype , Humans , Cohort Studies , DNA Methylation/genetics , Male , Female , Middle Aged , Smoking/genetics , Genomics/methods , Adult , Computational Biology/methods , CpG Islands/genetics , Aged , MultiomicsABSTRACT
BACKGROUND: Hepatitis B virus (HBV) infection poses a substantial threat to human health, impacting not only infected individuals but also potentially exerting adverse effects on the health of their offspring. The underlying mechanisms driving this phenomenon remain elusive. This study aims to shed light on this issue by examining alterations in paternally imprinted genes within sperm. METHODS: A cohort of 35 individuals with normal semen analysis, comprising 17 hepatitis B surface antigen (HBsAg)-positive and 18 negative individuals, was recruited. Based on the previous research and the Online Mendelian Inheritance in Man database (OMIM, https://www.omim.org/ ), targeted promoter methylation sequencing was employed to investigate 28 paternally imprinted genes associated with various diseases. RESULTS: Bioinformatic analyses revealed 42 differentially methylated sites across 29 CpG islands within 19 genes and four differentially methylated CpG islands within four genes. At the gene level, an increase in methylation of DNMT1 and a decrease in methylation of CUL7, PRKAG2, and TP53 were observed. DNA methylation haplotype analysis identified 51 differentially methylated haplotypes within 36 CpG islands across 22 genes. CONCLUSIONS: This is the first study to explore the effects of HBV infection on sperm DNA methylation and the potential underlying mechanisms of intergenerational influence of paternal HBV infection.
Subject(s)
CpG Islands , DNA Methylation , Genomic Imprinting , Hepatitis B virus , Hepatitis B , Promoter Regions, Genetic , Spermatozoa , Humans , Male , DNA Methylation/genetics , Promoter Regions, Genetic/genetics , Spermatozoa/metabolism , CpG Islands/genetics , Genomic Imprinting/genetics , Hepatitis B/genetics , Hepatitis B/virology , Adult , Hepatitis B virus/genetics , Haplotypes/genetics , Middle AgedABSTRACT
The time from conception through the first year of life is the most dynamic period in human development. This time period is particularly important for infants born very preterm (< 30 weeks gestation; VPT), as they experience a significant disruption in the normal developmental trajectories and are at heightened risk of experiencing developmental impairments and delays. Variations in the epigenetic landscape during this period may reflect this disruption and shed light on the interrelationships between aging, maturation, and the epigenome. We evaluated how gestational age (GA) and age since conception in neonates [post-menstrual age (PMA)], were related to DNA methylation in buccal cells collected at NICU discharge from VPT infants (n = 538). After adjusting for confounders and applying Bonferroni correction, we identified 2,366 individual CpGs associated with GA and 14,979 individual CpGs associated with PMA, as well as multiple differentially methylated regions. Pathway enrichment analysis identified pathways involved in axonogenesis and regulation of neuron projection development, among many other growth and developmental pathways (FDR q < 0.001). Our findings align with prior work, and also identify numerous novel associations, suggesting that genes important in growth and development, particularly neurodevelopment, are subject to substantial epigenetic changes during early development among children born VPT.
Subject(s)
DNA Methylation , Epigenesis, Genetic , Gestational Age , Humans , Infant, Newborn , Female , Male , Infant, Extremely Premature/growth & development , CpG Islands , InfantABSTRACT
Background: Maternal smoking has been linked to adverse health outcomes in newborns but the extent to which it impacts newborn health has not been quantified through an aggregated cord blood DNA methylation (DNAm) score. Here, we examine the feasibility of using cord blood DNAm scores leveraging large external studies as discovery samples to capture the epigenetic signature of maternal smoking and its influence on newborns in White European and South Asian populations. Methods: We first examined the association between individual CpGs and cigarette smoking during pregnancy, and smoking exposure in two White European birth cohorts (n=744). Leveraging established CpGs for maternal smoking, we constructed a cord blood epigenetic score of maternal smoking that was validated in one of the European-origin cohorts (n=347). This score was then tested for association with smoking status, secondary smoking exposure during pregnancy, and health outcomes in offspring measured after birth in an independent White European (n=397) and a South Asian birth cohort (n=504). Results: Several previously reported genes for maternal smoking were supported, with the strongest and most consistent association signal from the GFI1 gene (6 CpGs with p<5 × 10-5). The epigenetic maternal smoking score was strongly associated with smoking status during pregnancy (OR = 1.09 [1.07, 1.10], p=5.5 × 10-33) and more hours of self-reported smoking exposure per week (1.93 [1.27, 2.58], p=7.8 × 10-9) in White Europeans. However, it was not associated with self-reported exposure (p>0.05) among South Asians, likely due to a lack of smoking in this group. The same score was consistently associated with a smaller birth size (-0.37±0.12 cm, p=0.0023) in the South Asian cohort and a lower birth weight (-0.043±0.013 kg, p=0.0011) in the combined cohorts. Conclusions: This cord blood epigenetic score can help identify babies exposed to maternal smoking and assess its long-term impact on growth. Notably, these results indicate a consistent association between the DNAm signature of maternal smoking and a small body size and low birth weight in newborns, in both White European mothers who exhibited some amount of smoking and in South Asian mothers who themselves were not active smokers. Funding: This study was funded by the Canadian Institutes of Health Research Metabolomics Team Grant: MWG-146332.
Subject(s)
Asian People , DNA Methylation , Epigenesis, Genetic , White People , Humans , Female , DNA Methylation/genetics , Pregnancy , Infant, Newborn , White People/genetics , Asian People/genetics , Smoking/genetics , Smoking/adverse effects , Male , Fetal Blood , Adult , Cohort Studies , CpG Islands , Prenatal Exposure Delayed Effects/geneticsABSTRACT
Differentially methylated CpG sites (dmCpGs) that distinguish prostate tumour from adjacent benign tissue could aid in the diagnosis and prognosis of prostate cancer. Previously, the identification of such dmCpGs has only been undertaken in radical prostatectomy (RP) samples and not primary diagnostic tumour samples (needle biopsy or transurethral resection of the prostate). We interrogated an Australian dataset comprising 125 tumour and 43 adjacent histologically benign diagnostic tissue samples, including 41 paired samples, using the Infinium Human Methylation450 BeadChip. Regression analyses of paired tumour and adjacent benign samples identified 2,386 significant dmCpGs (Bonferroni p < 0.01; delta-ß ≥ 40%), with LASSO regression selecting 16 dmCpGs that distinguished tumour samples in the full Australian diagnostic dataset (AUC = 0.99). Results were validated in independent North American (npaired = 19; AUC = 0.87) and The Cancer Genome Atlas (TCGA; npaired = 50; AUC = 0.94) RP datasets. Two of the 16 dmCpGs were in genes that were significantly down-regulated in Australian tumour samples (Bonferroni p < 0.01; GSTM2 and PRKCB). Ten additional dmCpGs distinguished low (n = 34) and high Gleason (n = 88) score tumours in the diagnostic Australian dataset (AUC = 0.95), but these performed poorly when applied to the RP datasets (North American: AUC = 0.66; TCGA: AUC = 0.62). The DNA methylation marks identified here could augment and improve current diagnostic tests and/or form the basis of future prognostic tests.
Subject(s)
CpG Islands , DNA Methylation , Prostatic Neoplasms , Humans , Prostatic Neoplasms/genetics , Prostatic Neoplasms/pathology , Prostatic Neoplasms/diagnosis , Prostatic Neoplasms/surgery , Prostatic Neoplasms/metabolism , Male , CpG Islands/genetics , Aged , Middle Aged , Prostatectomy , Biomarkers, Tumor/genetics , Gene Expression Regulation, Neoplastic , Australia , PrognosisABSTRACT
BACKGROUND: Diesel exhaust particles (DEP), which contain hazardous compounds, are emitted during the combustion of diesel. As approximately one-third of the vehicles worldwide use diesel, there are growing concerns about the risks posed by DEP to human health. Long-term exposure to DEP is associated with airway hyperresponsiveness, pulmonary fibrosis, and inflammation; however, the molecular mechanisms behind the effects of DEP on the respiratory tract are poorly understood. Such mechanisms can be addressed by examining transcriptional and DNA methylation changes. Although several studies have focused on the effects of short-term DEP exposure on gene expression, research on the transcriptional effects and genome-wide DNA methylation changes caused by long-term DEP exposure is lacking. Hence, in this study, we investigated transcriptional and DNA methylation changes in human adenocarcinoma alveolar basal epithelial A549 cells caused by prolonged exposure to DEP and determined whether these changes are concordant. RESULTS: DNA methylation analysis using the Illumina Infinium MethylationEPIC BeadChips showed that the methylation levels of DEP-affected CpG sites in A549 cells changed in a dose-dependent manner; the extent of change increased with increasing dose reaching the statistical significance only in samples exposed to 30 µg/ml DEP. Four-week exposure to 30 µg/ml of DEP significantly induced DNA hypomethylation at 24,464 CpG sites, which were significantly enriched for DNase hypersensitive sites, genomic regions marked by H3K4me1 and H3K27ac, and several transcription factor binding sites. In contrast, 9,436 CpG sites with increased DNA methylation levels were significantly overrepresented in genomic regions marked by H3K27me3 as well as H3K4me1 and H3K27ac. In parallel, gene expression profiling by RNA sequencing demonstrated that long-term exposure to DEP altered the expression levels of 2,410 genes, enriching 16 gene sets including Xenobiotic metabolism, Inflammatory response, and Senescence. In silico analysis revealed that the expression levels of 854 genes correlated with the methylation levels of the DEP-affected cis-CpG sites. CONCLUSIONS: To our knowledge, this is the first report of genome-wide transcriptional and DNA methylation changes and their associations in A549 cells following long-term exposure to DEP.
Subject(s)
DNA Methylation , Transcriptome , Vehicle Emissions , Humans , DNA Methylation/drug effects , Vehicle Emissions/toxicity , A549 Cells , Transcriptome/drug effects , Alveolar Epithelial Cells/metabolism , Alveolar Epithelial Cells/drug effects , CpG Islands , Particulate Matter/toxicity , Lung Neoplasms/genetics , Lung Neoplasms/pathology , Lung Neoplasms/chemically induced , Lung Neoplasms/metabolismABSTRACT
Circulating cell-free DNA (cfDNA) is emerging as an avenue for cancer detection, but the characteristics of cfDNA fragmentation in the blood are poorly understood. We evaluate the effect of DNA methylation and gene expression on genome-wide cfDNA fragmentation through analysis of 969 individuals. cfDNA fragment ends more frequently contained CCs or CGs, and fragments ending with CGs or CCGs are enriched or depleted, respectively, at methylated CpG positions. Higher levels and larger sizes of cfDNA fragments are associated with CpG methylation and reduced gene expression. These effects are validated in mice with isogenic tumors with or without the mutant IDH1, and are associated with genome-wide changes in cfDNA fragmentation in patients with cancer. Tumor-related hypomethylation and increased gene expression are associated with decrease in cfDNA fragment size that may explain smaller cfDNA fragments in human cancers. These results provide a connection between epigenetic changes and cfDNA fragmentation with implications for disease detection.
Subject(s)
Cell-Free Nucleic Acids , CpG Islands , DNA Fragmentation , DNA Methylation , Neoplasms , Humans , Cell-Free Nucleic Acids/genetics , Cell-Free Nucleic Acids/blood , Animals , Mice , CpG Islands/genetics , Neoplasms/genetics , Epigenesis, Genetic , Female , Isocitrate Dehydrogenase/genetics , Male , Gene Expression Regulation, NeoplasticABSTRACT
BACKGROUND: Renal cell carcinoma (RCC), one of the most fatal urologic tumors, accounts for approximately 3% of all adult cancers and exhibits a high metastatic index at diagnosis and a high rate of relapse. Radical or partial nephrectomy is a curative option for nonmetastatic RCCs. Targeted therapy has been shown to improve the survival of patients with metastatic RCCs. However, the underlying cellular and molecular events associated with RCC pathogenesis are not well known. METHODS: To investigate the clinical role of the transcription factor activator protein (AP)-2α in RCC, methylated CpG island recovery assays and microarray analysis were employed. COBRA and RTâqPCR assays were performed to assess AP-2α expression in RCC. RESULTS: A negative correlation was noted between AP-2α mRNA expression levels and methylation status. Multivariate analyses showed that AP-2α mRNA was a major risk factor not only for overall and disease-free survival in RCC but also for disease-free survival in clear cell RCC. CONCLUSIONS: Our results indicated that AP-2α expression was deregulated in RCC and associated with overall patient survival and disease-free survival. Such findings suggest that AP-2α might play an important role in the pathogenesis of RCC.
Subject(s)
Carcinoma, Renal Cell , DNA Methylation , Gene Expression Regulation, Neoplastic , Kidney Neoplasms , Transcription Factor AP-2 , Humans , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/mortality , Carcinoma, Renal Cell/pathology , Transcription Factor AP-2/genetics , Transcription Factor AP-2/metabolism , Male , Female , Kidney Neoplasms/genetics , Kidney Neoplasms/mortality , Kidney Neoplasms/pathology , Middle Aged , Aged , CpG Islands/genetics , Adult , Prognosis , Disease-Free Survival , RNA, Messenger/genetics , RNA, Messenger/metabolismABSTRACT
BACKGROUND: While the association of chronological age with DNA methylation (DNAm) in whole blood has been extensively studied, the tissue-specificity of age-related DNAm changes remains an active area of research. Studies investigating the association of age with DNAm in tissues such as brain, skin, immune cells, fat, and liver have identified tissue-specific and non-specific effects, thus, motivating additional studies of diverse human tissue and cell types. RESULTS: Here, we performed an epigenome-wide association study, leveraging DNAm data (Illumina EPIC array) from 961 tissue samples representing 9 tissue types (breast, lung, colon, ovary, prostate, skeletal muscle, testis, whole blood, and kidney) from the Genotype-Tissue Expression (GTEx) project. We identified age-associated CpG sites (false discovery rate < 0.05) in 8 tissues (all except skeletal muscle, n = 47). This included 162,002 unique hypermethylated and 90,626 hypomethylated CpG sites across all tissue types, with 130,137 (80%) hypermethylated CpGs and 74,703 (82%) hypomethylated CpG sites observed in a single tissue type. While the majority of age-associated CpG sites appeared tissue-specific, the patterns of enrichment among genomic features, such as chromatin states and CpG islands, were similar across most tissues, suggesting common mechanisms underlying cellular aging. Consistent with previous findings, we observed that hypermethylated CpG sites are enriched in regions with repressed polycomb signatures and CpG islands, while hypomethylated CpG sites preferentially occurred in non-CpG islands and enhancers. To gain insights into the functional effects of age-related DNAm changes, we assessed the correlation between DNAm and local gene expression changes to identify age-related expression quantitative trait methylation (age-eQTMs). We identified several age-eQTMs present in multiple tissue-types, including in the CDKN2A, HENMT1, and VCWE regions. CONCLUSION: Overall, our findings will aid future efforts to develop biomarkers of aging and understand mechanisms of aging in diverse human tissue types.
Subject(s)
Aging , CpG Islands , DNA Methylation , Organ Specificity , Humans , Aging/genetics , Female , Male , Adult , Genome-Wide Association Study , Middle Aged , Aged , Epigenesis, Genetic , EpigenomeABSTRACT
Structural variation heavily influences the molecular landscape of cancer, in part by impacting DNA methylation-mediated transcriptional regulation. Here, using multi-omic datasets involving >2400 pediatric brain and central nervous system tumors of diverse histologies from the Children's Brain Tumor Network, we report hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of somatic structural variant (SV) breakpoints is recurrently associated with altered expression or DNA methylation, respectively, including tumor suppressor genes ATRX and CDKN2A. Altered DNA methylation near enhancers associates with nearby somatic SV breakpoints, including MYC and MYCN. A subset of genes with SV-CGI methylation associations also have expression associations with patient survival, including BCOR, TERT, RCOR2, and PDLIM4. DNA methylation changes in recurrent or progressive tumors compared to the initial tumor within the same patient can predict survival in pediatric and adult cancers. Our comprehensive and pan-histology genomic analyses reveal mechanisms of noncoding alterations impacting cancer genes.
Subject(s)
Brain Neoplasms , CpG Islands , DNA Methylation , Gene Expression Regulation, Neoplastic , Humans , DNA Methylation/genetics , Brain Neoplasms/genetics , Brain Neoplasms/mortality , Brain Neoplasms/pathology , CpG Islands/genetics , Child , X-linked Nuclear Protein/genetics , X-linked Nuclear Protein/metabolism , Epigenome , Cyclin-Dependent Kinase Inhibitor p16/genetics , Cyclin-Dependent Kinase Inhibitor p16/metabolism , N-Myc Proto-Oncogene Protein/genetics , N-Myc Proto-Oncogene Protein/metabolism , Proto-Oncogene Proteins c-myc/genetics , Proto-Oncogene Proteins c-myc/metabolism , Male , Telomerase/genetics , FemaleABSTRACT
Precisely defining and mapping all cytosine (C) positions and their clusters, known as CpG islands (CGIs), as well as their methylation status, are pivotal for genome-wide epigenetic studies, especially when population-centric reference genomes are ready for timely application. Here, we first align the two high-quality reference genomes, T2T-YAO and T2T-CHM13, from different ethnic backgrounds in a base-by-base fashion and compute their genome-wide density-defined and position-defined CGIs. Second, by mapping some representative genome-wide methylation data from selected organs onto the two genomes, we find that there are about 4.7%-5.8% sequence divergency of variable categories depending on quality cutoffs. Genes among the divergent sequences are mostly associated with neurological functions. Moreover, CGIs associated with the divergent sequences are significantly different with respect to CpG density and observed CpG/expected CpG (O/E) ratio between the two genomes. Finally, we find that the T2T-YAO genome not only has a greater CpG coverage than that of the T2T-CHM13 genome when whole-genome bisulfite sequencing (WGBS) data from the European and American populations are mapped to each reference, but also shows more hyper-methylated CpG sites as compared to the T2T-CHM13 genome. Our study suggests that future genome-wide epigenetic studies of the Chinese populations rely on both acquisition of high-quality methylation data and subsequent precision CGI mapping based on the Chinese T2T reference.
Subject(s)
CpG Islands , DNA Methylation , Genome, Human , CpG Islands/genetics , DNA Methylation/genetics , Humans , Genome, Human/genetics , Chromosome Mapping/methodsABSTRACT
Recent nanopore sequencing system (R10.4) has enhanced base calling accuracy and is being increasingly utilized for detecting CpG methylation state. However, the robustness and universality of the methylation calling model in officially supplied Dorado remains poorly tested. In this study, we obtained heterogeneous datasets from human and plant sources to carry out comprehensive evaluations, which showed that Dorado performed significantly different across datasets. We therefore developed deep neural networks and implemented several optimizations in training a new model called DeepBAM. DeepBAM achieved superior and more stable performances compared with Dorado, including higher area under the ROC curves (98.47% on average and up to 7.36% improvement) and F1 scores (94.97% on average and up to 16.24% improvement) across the datasets. DeepBAM-based whole genome methylation frequencies have achieved >0.95 correlations with BS-seq on four of five datasets, outperforming Dorado in all instances. It enables unraveling allele-specific methylation patterns, including regions of transposable elements. The enhanced performance of DeepBAM paves the way for broader applications of nanopore sequencing in CpG methylation studies.
Subject(s)
CpG Islands , DNA Methylation , Nanopore Sequencing , Nanopore Sequencing/methods , Humans , Software , Sequence Analysis, DNA/methods , Neural Networks, ComputerABSTRACT
BACKGROUND: The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role. METHODS AND RESULTS: Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR < 0.05), primarily within CpG islands and gene promoters. Dysregulated genes highlighted potential links to glutamate/glutamine metabolism, which may be relevant to PASC symptoms. Key genes with potential significance to COVID-19 infection and long-term effects include GLUD1, ATP1A3, and ARRB2. Furthermore, Horvath's epigenetic clock showed a slight but significant age acceleration in post-COVID-19 patients. We also observed a substantial increase in stochastic epigenetic mutations (SEMs) in the post-COVID-19 group, implying potential epigenetic drift. SEM analysis identified 790 affected genes, indicating dysregulation in pathways related to insulin resistance, VEGF signaling, apoptosis, hypoxia response, T-cell activation, and endothelin signaling. CONCLUSIONS: Our study provides valuable insights into the epigenetic consequences of COVID-19. Results suggest possible associations with accelerated aging, epigenetic drift, and the disruption of critical biological pathways linked to insulin resistance, immune response, and vascular health. Understanding these epigenetic changes could be crucial for elucidating the complex mechanisms behind long-COVID and developing targeted therapeutic interventions.
Subject(s)
COVID-19 , CpG Islands , DNA Methylation , Epigenesis, Genetic , SARS-CoV-2 , Humans , DNA Methylation/genetics , COVID-19/genetics , Epigenesis, Genetic/genetics , Male , Female , Middle Aged , CpG Islands/genetics , Adult , Aging/genetics , Aged , Genome-Wide Association Study/methods , Post-Acute COVID-19 Syndrome , ItalyABSTRACT
BACKGROUND: Gestational DNA methylation age (GAmAge) has been developed and validated in European ancestry samples. Its applicability to other ethnicities and associations with fetal stress and newborn phenotypes such as inflammation markers are still to be determined. This study aims to examine the applicability of GAmAge developed from cord blood samples of European decedents to a racially diverse birth cohort, and associations with newborn phenotypes. METHODS: GAmAge based on 176 CpGs (Haftorn GAmAge) was calculated for 940 children from a US predominantly urban, low-income, multiethnic birth cohort. Cord blood DNA methylation was profiled by Illumina EPIC array. Newborn phenotypes included anthropometric measurements and, for a subset of newborns (N = 194), twenty-seven cord blood inflammatory markers (sandwich immunoassays). RESULTS: GAmAge had a stronger correlation with GEAA in boys (r = 0.89, 95% confidence interval (CI) [0.87,0.91]) compared with girls (r = 0.83, 95% CI [0.80,0.86]), and was stronger among extremely preterm to very preterm babies (r = 0.91, 95% CI [0.81,0.96]), compared with moderate (r = 0.48, 95% CI [0.34,0.60]) and term babies (r = 0.58, 95% CI [0.53,0.63]). Among White newborns (N = 51), the correlation between GAmAge vs. GEAA was slightly stronger (r = 0.89, 95% CI [0.82,0.94]) compared with Black/African American newborns (N = 668; r = 0.87, 95% CI [0.85,0.89]) or Hispanic (N = 221; r = 0.79, 95% CI [0.74,0.84]). Adjusting for GEAA and sex, GAmAge was associated with anthropometric measurements, cord blood brain-derived neurotrophic factor (BDNF), and monocyte chemoattractant protein-1 (MCP-1) (p < 0.05 for all). CONCLUSIONS: GAmAge estimation is robust across different populations and racial/ethnic subgroups. GAmAge may be utilized as a proxy for GEAA and for assessing fetus development, indicated by inflammatory state and birth outcomes.
Subject(s)
DNA Methylation , Fetal Blood , Fetal Development , Gestational Age , Humans , Female , Male , DNA Methylation/genetics , Infant, Newborn , Pregnancy , Fetal Development/genetics , Fetal Blood/chemistry , Boston , Birth Cohort , Adult , Biomarkers/blood , White People/genetics , CpG Islands/genetics , Epigenesis, Genetic , Pregnancy Outcome/geneticsABSTRACT
BACKGROUND: Current research on the epigenetic repercussions of exposure to a combination of pollutants is limited. This study aims to discern DNA methylation probes associated with exposure to multiple pollutants, serving as early effect markers, and single-nucleotide polymorphisms (SNPs) as surrogate indicators for population susceptibility. The investigation involved the analysis of urine exposure biomarkers for 11 heavy metals (vanadium, arsenic, mercury, cadmium, chromium, nickel, lead, manganese, copper, strontium, thallium), polycyclic aromatic hydrocarbon (PAHs) (1-hydroxypyrene), genome-wide DNA methylation sequencing, and SNPs array on all study participants. The data were integrated with metabolomics information and analyzed both at a community level based on proximity to home addresses relative to the complex and at an individual level based on exposure biomarker concentrations. RESULTS: On a community level, 67 exposure-related CpG probes were identified, while 70 CpG probes were associated with urine arsenic concentration, 2 with mercury, and 46 with vanadium on an individual level. These probes were annotated to genes implicated in cancers and chronic kidney disease. Weighted quantile sum regression analysis revealed that vanadium, mercury, and 1-hydroxypyrene contributed the most to cg08238319 hypomethylation. cg08238319 is annotated to the aryl hydrocarbon receptor repressor (AHRR) gene, and AHRR hypomethylation was correlated with an elevated risk of lung cancer. AHRR was further linked to deregulations in phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, along with heightened oxidative stress. Additionally, three SNPs (rs11085020, rs199442, and rs10947050) corresponding to exposure-related CpG probes exhibited significant interaction effects with multiple heavy metals and PAHs exposure, and have been implicated in cancer progression and respiratory diseases. CONCLUSION: Our findings underscore the pivotal role of AHRR methylation in gene-environment interactions and highlight SNPs that could potentially serve as indicators of population susceptibility in regions exposed to multiple heavy metals and PAHs.
Subject(s)
DNA Methylation , Environmental Exposure , Metals, Heavy , Polymorphism, Single Nucleotide , Humans , DNA Methylation/drug effects , DNA Methylation/genetics , Male , Female , Environmental Exposure/adverse effects , Metals, Heavy/urine , Metals, Heavy/adverse effects , Middle Aged , Adult , CpG Islands/genetics , Polycyclic Aromatic Hydrocarbons/urine , Polycyclic Aromatic Hydrocarbons/adverse effects , Epigenesis, Genetic/drug effects , Epigenesis, Genetic/genetics , Biomarkers/urine , Pyrenes/urine , Environmental Pollutants/urine , Environmental Pollutants/adverse effects , Basic Helix-Loop-Helix Transcription Factors/genetics , Repressor ProteinsABSTRACT
Epithelial ovarian cancer (EOC) is the deadliest women's cancer and has a poor prognosis. Early detection is the key for improving survival (a 5-year survival rate in stage I/II is over 70% compared to that of 25% in stage III/IV) and can be achieved through methylation markers from circulating cell-free DNA (cfDNA) using a liquid biopsy. In this study, we first identify top 500 EOC markers differentiating EOC from healthy female controls from 3.3 million methylome-wide CpG sites and validated them in 1,800 independent cfDNA samples. We then utilize a pretrained AI transformer system called MethylBERT to develop an EOC diagnostic model which achieves 80% sensitivity and 95% specificity in early-stage EOC diagnosis. We next develop a simple digital droplet PCR (ddPCR) assay which archives good performance, facilitating early EOC detection.
Subject(s)
Biomarkers, Tumor , Cell-Free Nucleic Acids , DNA Methylation , Early Detection of Cancer , Ovarian Neoplasms , Humans , Female , DNA Methylation/genetics , Biomarkers, Tumor/genetics , Ovarian Neoplasms/genetics , Ovarian Neoplasms/diagnosis , Ovarian Neoplasms/blood , Early Detection of Cancer/methods , Cell-Free Nucleic Acids/genetics , Cell-Free Nucleic Acids/blood , Carcinoma, Ovarian Epithelial/genetics , Carcinoma, Ovarian Epithelial/diagnosis , Carcinoma, Ovarian Epithelial/pathology , Artificial Intelligence , CpG Islands/genetics , Middle Aged , Liquid Biopsy/methodsABSTRACT
In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.
Subject(s)
Phenotype , Humans , Male , Female , Metabolomics/methods , Diabetes Mellitus/genetics , Diabetes Mellitus/metabolism , DNA Methylation , Transcriptome , Middle Aged , Genome-Wide Association Study , Qatar/epidemiology , Epigenome , Adult , CpG Islands/genetics , Diabetes Mellitus, Type 2/genetics , Diabetes Mellitus, Type 2/metabolism , MultiomicsABSTRACT
INTRODUCTION: Men with African ancestry have the highest incidence and mortality rates of prostate cancer (PCa) worldwide. METHODS: This study aimed to identify differentially methylated genes between tumor vs. adjacent normal and aggressive vs. indolent PCa in 121 African American patients. Epigenome-wide DNA methylation patterns in tumor DNA were assessed using the human Illumina Methylation EPIC V1 array. RESULTS: Around 5,139 differentially methylated CpG-sites (q < 0.01, lΔßl > 0.2) were identified when comparing normal vs. tumor, with an overall trend of hypermethylation in prostate tumors. Multiple representative differentially methylated regions (DMRs), including immune-related genes, such as CD40, Galectin3, OX40L, and STING, were detected in prostate tumors when compared to adjacent normal tissues. Based on an epigenetic clock model, we observed that tumors' total number of stem cell divisions and the stem cell division rate were significantly higher than adjacent normal tissues. Regarding PCa aggressiveness, 2,061 differentially methylated CpG-sites (q < 0.05, lΔßl > .05) were identified when the grade group (GG)1 was compared with GG4/5. Among these 2,061 CpG sites, 155 probes were consistently significant in more than one comparison. Among these genes, several immune system genes, such as COL18A1, S100A2, ITGA4, HLA-C, and ADCYAP1, have previously been linked to tumor progression in PCa. CONCLUSION: Several differentially methylated genes involved in immune-oncologic pathways associated with disease risk or aggressiveness were identified. In addition, 261 African American-specific differentially methylated genes related to the risk of PCa were identified. These results can shedlight on potential mechanisms contributing to PCa disparities in the African American Population.
Subject(s)
Black or African American , DNA Methylation , Genome-Wide Association Study , Prostatic Neoplasms , Humans , Male , Black or African American/genetics , Prostatic Neoplasms/genetics , Prostatic Neoplasms/pathology , Prostatic Neoplasms/ethnology , Middle Aged , Aged , Epigenome , CpG Islands , Epigenesis, Genetic , Gene Expression Regulation, Neoplastic , Biomarkers, Tumor/geneticsABSTRACT
In patients with proximal hypospadias, often no genetic cause is identified despite extensive genetic testing. Many genes involved in sex development encode transcription factors with strict timing and dosing of the gene products. We hypothesised that there might be recurrent differences in DNA methylation in boys with hypospadias and that these might differ between patients born small versus appropriate for gestational age. Genome-wide Methylated DNA sequencing (MeD-seq) was performed on 32bp LpnPI restriction enzyme fragments after RE-digestion in leucocytes from 16 XY boys with unexplained proximal hypospadias, one with an unexplained XX testicular disorder/difference of sex development (DSD) and twelve, healthy, sex- and age-matched controls. Five of seven differentially methylated regions (DMRs) between patients and XY controls were in the Long Intergenic Non-Protein Coding RNA 665 (LINC00665; CpG24525). Three patients showed hypermethylation of MAP3K1. Finally, no DMRs in XX testicular DSD associated genes were identified in the XX boy versus XX controls. In conclusion, we observed no recognizable epigenetic signature in 16 boys with XY proximal hypospadias and no difference between children born small versus appropriate for gestational age. Comparison to previous methylation studies in individuals with hypospadias did not show consistent findings, possibly due to the use of different inclusion criteria, tissues and methods.
Subject(s)
DNA Methylation , Hypospadias , Humans , Male , Hypospadias/genetics , Pilot Projects , Epigenesis, Genetic , CpG Islands , RNA, Long Noncoding/genetics , Child , Child, Preschool , Infant , Genome-Wide Association Study , Case-Control StudiesABSTRACT
BACKGROUND: The plasma metabolome reflects the physiological state of various biological processes and can serve as a proxy for disease risk. Plasma metabolite variation, influenced by genetic and epigenetic mechanisms, can also affect the cellular microenvironment and blood cell epigenetics. The interplay between the plasma metabolome and the blood cell epigenome remains elusive. In this study, we performed an epigenome-wide association study (EWAS) of 1183 plasma metabolites in 693 participants from the LifeLines-DEEP cohort and investigated the causal relationships in DNA methylation-metabolite associations using bidirectional Mendelian randomization and mediation analysis. RESULTS: After rigorously adjusting for potential confounders, including genetics, we identified five robust associations between two plasma metabolites (L-serine and glycine) and three CpG sites located in two independent genomic regions (cg14476101 and cg16246545 in PHGDH and cg02711608 in SLC1A5) at a false discovery rate of less than 0.05. Further analysis revealed a complex bidirectional relationship between plasma glycine/serine levels and DNA methylation. Moreover, we observed a strong mediating role of DNA methylation in the effect of glycine/serine on the expression of their metabolism/transport genes, with the proportion of the mediated effect ranging from 11.8 to 54.3%. This result was also replicated in an independent population-based cohort, the Rotterdam Study. To validate our findings, we conducted in vitro cell studies which confirmed the mediating role of DNA methylation in the regulation of PHGDH gene expression. CONCLUSIONS: Our findings reveal a potential feedback mechanism in which glycine and serine regulate gene expression through DNA methylation.