Measured DNA Methylation Research Articles

Genetic Architecture of Immune Cell DNA Methylation in the Rhesus Macaque.

Genetic variation that impacts gene regulation, rather than protein function, can have strong effects on trait variation both within and between species. Epigenetic mechanisms, such as DNA methylation, are often an important intermediate link between genotype and phenotype, yet genetic effects on DNA methylation remain understudied in natural populations. To address this gap, we used reduced representation bisulfite sequencing to measure DNA methylation levels at 555,856 CpGs in peripheral whole blood of 573 samples collected from free-ranging rhesus macaques (Macaca mulatta) living on the island of Cayo Santiago, Puerto Rico. We used allele-specific methods to map cis-methylation quantitative trait loci (meQTL) and tested for effects of 243,389 single nucleotide polymorphisms (SNPs) on local DNA methylation levels. Of 776,092 tested SNP-CpG pairs, we identified 516,213 meQTL, with 69.12% of CpGs having at least one meQTL (FDR < 5%). On average, meQTL explained 21.2% of nearby methylation variance, significantly more than age or sex. meQTL were enriched in genomic compartments where methylation is likely to impact gene expression, for example, promoters, enhancers and binding sites for methylation-sensitive transcription factors. In support, using mRNA-seq data from 172 samples, we confirmed 332 meQTL as whole blood cis-expression QTL (eQTL) in the population, and found meQTL-eQTL genes were enriched for immune response functions, like antigen presentation and inflammation. Overall, our study takes an important step towards understanding the genetic architecture of DNA methylation in natural populations, and more generally points to the biological mechanisms driving phenotypic variation in our close relatives.

Technical variability across the 450K, EPICv1, and EPICv2 DNA methylation arrays: lessons learned for clinical and longitudinal studies

DNA methylation (DNAm) is the most commonly measured epigenetic mechanism in human populations, with most studies using Illumina arrays to assess DNAm levels. In 2023, Illumina updated their DNAm arrays to the EPIC version 2 (EPICv2), building on prior iterations, namely the EPIC version 1 (EPICv1) and 450K arrays. Whether DNAm measurements are stable across these three generations of arrays has yet not been investigated, limiting the ability of researchers—especially those with longitudinal data—to compare and replicate results across arrays. Here, we present results from a study of 30 child participants (15 male; 15 female) from the Drakenstein Child Health Study, who had DNAm measured on all three of the latest arrays: 450K, EPICv1, and EPICv2. Using these data, we created an annotation of probe quality across arrays, which includes the intraclass correlations, interquartile ranges, correlations, and array bias (i.e., the extent to which DNAm levels were explained by array type) of all CpGs. We also present results from an analysis of sex differences, where we found that CpGs with lower replicability across arrays had higher array-based variance, suggesting this variance metric help guide replication efforts. We also showed that epigenetic age estimates across arrays were more stable when using the principal component versions of epigenetic clocks. Ultimately, this collection of results provides a framework for investigating the replicability and longitudinal stability of epigenetic changes across multiple versions of Illumina DNAm arrays.

An Outline of a Simple, Interpretable Epigenetic Composite Score for Mortality Prediction for Accelerated Underwriting.

In principle, it is generally accepted that DNA methylation measures can be used to predict mortality. However, as of yet, no epigenetic metric has been successfully incorporated into underwriting procedures. In part, this failure results from the relative incompatibility of many DNA methylation measures with conventional underwriting practices. To test the ability of previously established epigenetic markers of smoking, drinking and diabetes to standard lipid-based approaches for predicting mortality. We constructed a series of Cox proportional hazards models for mortality using clinical data and DNA methylation data from 4 previously described loci from the Framingham Heart Study. The incorporation of vital signs, standard lipid and diabetes laboratory assessments to a base model consisting of age and sex only modestly increased prediction of mortality from 0.732 to 0.741 area under the curve (AUC). However, the addition of epigenetic marker information for smoking and drinking to the base model markedly increased prediction (AUC=0.787) while the addition of epigenetic marker for diabetes increased prediction even further (AUC=0.792). These results demonstrate the potential of simple interpretable, epigenetic models to predict mortality in a manner compatible with standard underwriting procedures. Potentially, this epigenetic approach using rapid methylation sensitive digital PCR procedures that can utilize saliva or whole blood DNA would increase prediction power even further while facilitating more accurate accelerated underwriting assessments of mortality.

DNA methylation age acceleration is associated with incident cognitive impairment in the Health and Retirement Study.

DNA methylation clocks have emerged as promising biomarkers for cognitive impairment and dementia. Longitudinal studies exploring the link between DNA methylation clocks and cognitive decline have been constrained by limited sample sizes and a lack of diversity. Our study aimed to investigate the longitudinal associations between DNA methylation clocks and incident cognitive impairment using a larger sample size encompassing a US nationally representative sample from the Health and Retirement Study. We measured DNA methylation age acceleration in 2016 by comparing the residuals of DNA methylation clocks, including GrimAge, against chronological age. Cognitive decline was determined by the change in Langa-Weir cognition status from 2016 to 2018. Using multivariable logistic regression, we evaluated the link between DNA methylation age acceleration and cognitive decline, adjusting for cell-type proportions, demographic, and health factors. We also conducted an inverse probability weighting analysis to address potential selection bias from varying loss-to-follow-up rates. The analytic sample (N=2,713) at baseline had an average of 68 years old, and during the two years of follow-up, 12% experienced cognitive decline. Participants who experienced cognitive decline during follow-up had higher baseline GrimAge (mean = 1.2 years) acceleration compared to those who maintained normal cognitive function (mean = -0.8 years, p < 0.001). A one-year increase in GrimAge acceleration was associated with 1.05 times higher adjusted and survey-weighted odds of cognitive decline during follow-up (95% CI: 1.01-1.10). This association was consistent after accounting for loss-to-follow-up (OR = 1.07, 95% CI: 1.04-1.11). Our study offers insights into DNA methylation age acceleration associated with cognitive decline, suggesting avenues for improved prevention, diagnosis, and treatment.

Epigenetic Biomarker: Improving Estimates of Fetal Exposure to Cigarette Smoke.

The well-known cotinine test captures recent smoking, and survey responses are not always accurate. Now researchers propose a measure of DNA methylation in placental tissue that may be better than either.

Effects of DNA Methylation of HPA-Axis Genes of F1 Juvenile Induced by Maternal Density Stress on Behavior and Immune Traits in Root Voles (Microtus oeconomus)-A Field Experiment.

The literature shows that maternal stress can influence behavior and immune function in F1. Yet, most studies on these are from the laboratory, and replicated studies on the mechanisms by which maternal stress drives individual characteristics are still not fully understood in wild animals. We manipulated high- and low-density parental population density using large-scale field enclosures and examined behavior and immune traits. Within the field enclosures, we assessed anti-keyhole limpet hemocyanin immunoglobulin G (anti-KLH IgG) level, phytohemagglutinin (PHA) responses, hematology, cytokines, the depressive and anxiety-like behaviors and prevalence and intensity of coccidial infection. We then collected brain tissue from juvenile voles born at high or low density, quantified mRNA and protein expression of corticotropin-releasing hormone (CRH) and glucocorticoid receptor gene (NR3C1) and measured DNA methylation at CpG sites in a region that was highly conserved with the prairie vole CRH and NR3C1 promoter. At high density, we found that the F1 had a lower DNA methylation level of CRH and a higher DNA methylation level of NR3C1, which resulted in an increase in the expression levels of the CRH mRNA and protein expression and further reduced the expression levels of the NR3C1 mRNA and protein expression, and ultimately led to have delayed responses to acute immobilization stress. Juvenile voles born at high density also reduced anti-KLH IgG levels and PHA responses, increased cytokines, and depressive and anxiety-like behaviors, and the effects further led to higher coccidial infection. From the perspective of population density inducing the changes in behavior and immunity at the brain level, our results showed a physiological epigenetic mechanism for population self-regulation in voles. Our results indicate that altering the prenatal intrinsic stress environment can fundamentally impact behavior and immunity by DNA methylation of HPA-axis genes and can further drive population fluctuations in wild animals.

Blood Leukocyte DNA Methylation Markers of Periodontal Disease and Risk of Lung Cancer in a Case-Control Study Nested in the CLUE II Cohort.

Periodontal disease and DNA methylation markers have separately been associated with lung cancer risk. Examining methylation levels at genomic regions previously linked to periodontal disease may provide insights on the link between periodontal disease and lung cancer. In a nested case-control study drawn from the CLUE II cohort, we measured DNA methylation levels in 208 lung cancer cases and 208 controls. We examined the association between 37 DNA-methylated 5'-C-phosphate-G-3' (CpG) sites at three genomic regions, homeobox 4 (HOXA4), zinc finger protein (ZFP57), and a long noncoding RNA gene located in Chr10 (ENSG00000231601), and lung cancer risk. Statistically significant associations with lung cancer risk were observed for all 14 CpG sites from HOXA4 (OR ranging 1.41-1.62 for 1 SD increase in the DNA methylation level, especially within 15 years) and 1 CpG site on gene ENSG00000231601 (OR = 1.34 for 1 SD increase in the DNA methylation level). Although CpG sites on gene ZFP57 were not associated with lung cancer risk overall, statistically significant inverse associations were noted for six CpG sites when restricting follow-up to 15 years (OR = 0.73-0.77 for 1 SD increase in the DNA methylation level). Key methylation levels associated with periodontal disease are also associated with lung cancer risk. For both HOXA4 and ZFP57, the associations were stronger within 15 years of follow-up, which suggest that, if causal, the impact of methylation is acting late in the natural history of lung cancer. Identifying biological pathways that link periodontal disease and lung cancer could provide new opportunities for lung cancer detection and prevention.

Methyltransferase DNMT3B promotes colorectal cancer cell proliferation by inhibiting PLCG2.

Aberrant DNA methylation patterns in the promoter region of PLCG2 are associated with dysregulated signaling pathways and cellular functions. Its role in colorectal cancer cells is still unknown. In this study, qRT-PCR is used to measure DNMT3B expression in colorectal cancer. Western blot analysis and immunohistochemistry are used to analyze DNMT3B and PLCG2 protein levels in colorectal tissues and cell lines. Cell Counting Kit-8 (CCK-8) and colony formation assays are used to assess the proliferation of colorectal cancer cells. Methylation-specific PCR (MSP) and bisulfite-sequencing PCR (BSP) are used to measure DNA methylation level. Our results show that DNMT3B is overexpressed in colorectal cells in the TCGA datasets according to Kaplan-Meier plots. DNMT3B is significantly overexpressed in tumor tissues compared to that in adjacent nontumor tissues. Western blot analysis results demonstrate high expression of DNMT3B in tumor tissues. Compared to normal colonic epithelial cells, colorectal cancer cell lines exhibit elevated level of PLCG2 methylation. Overexpression of PLCG2 effectively prevents the growth of colorectal cancer xenograft tumors in vivo. PLCG2 is identified as a key downstream regulatory protein of DNMT3B in colorectal cancer. DNMT3B inhibits PLCG2 transcription through methylation of the PLCG2 promoter region. DNMT3B controls colorectal cancer cell proliferation through PLCG2, which is useful for developing therapeutic approaches that target PLCG2 expression for the treatment of colorectal cancer.

Hypomethylated leptin receptor reduces cerebral ischaemia-reperfusion injury by activating the JAK2/STAT3 signalling pathway.

To investigate the cerebroprotective effects of leptin in vitro and in vivo via the Janus kinase-2 (JAK2)/transcription factor signal transducer and activators of transcription-3 (STAT3) pathway and leptin receptors (LEPR). The study used the cellular oxygen-glucose deprivation (OGD) model in PC12 cells and the middle cerebral artery occlusion (MCAO) rat model of cerebral ischaemia-reperfusion injury (CIRI) to assess changes in gene expression and protein levels following leptin pretreatment. The methylated DNA immunoprecipitation (MeDIP) assay measured DNA methylation levels. The optimal leptin concentration for exerting neuroprotective effects against ischaemia-reperfusion injury in PC12 cells was 200 ng/ml in vitro, but excessive leptin diminished this effect. Leptin pretreatment in the MCAO rat model demonstrated a similar effect to previously reported leptin administration post-CIRI. In addition to regulating the expression of inflammation-related cytokines, Western blot analysis showed that leptin pretreatment upregulated BCL-2 and downregulated caspase 3 levels. The MeDIP analysis demonstrated that DNA methylation regulated LEPR gene expression in the MCAO rat model when leptin pretreatment was used. Exogenous leptin might bind to extra-activated LEPR by reducing the methylation level of the LEPR gene promoter region, which leads to an increase in phosphorylated JAK2/STAT3 and apoptotic signalling pathways.

Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans

BackgroundWe recently identified ~ 10,000 correlated regions of systemic interindividual epigenetic variation (CoRSIVs) in the human genome. These methylation variants are amenable to population studies, as DNA methylation measurements in blood provide information on epigenetic regulation throughout the body. Moreover, establishment of DNA methylation at human CoRSIVs is labile to periconceptional influences such as nutrition. Here, we analyze publicly available whole-genome bisulfite sequencing data on multiple tissues of each of two Holstein cows to determine whether CoRSIVs exist in cattle.ResultsFocusing on genomic blocks with ≥ 5 CpGs and a systemic interindividual variation index of at least 20, our approach identifies 217 cattle CoRSIVs, a subset of which we independently validate by bisulfite pyrosequencing. Similar to human CoRSIVs, those in cattle are strongly associated with genetic variation. Also as in humans, we show that establishment of DNA methylation at cattle CoRSIVs is particularly sensitive to early embryonic environment, in the context of embryo culture during assisted reproduction.ConclusionsOur data indicate that CoRSIVs exist in cattle, as in humans, suggesting these systemic epigenetic variants may be common to mammals in general. To the extent that individual epigenetic variation at cattle CoRSIVs affects phenotypic outcomes, assessment of CoRSIV methylation at birth may become an important tool for optimizing agriculturally important traits. Moreover, adjusting embryo culture conditions during assisted reproduction may provide opportunities to tailor agricultural outcomes by engineering CoRSIV methylation profiles.

Current evidence supporting associations of DNA methylation measurements with survivorship burdens in cancer survivors: A scoping review.

Identifying reliable biomarkers that reflect cancer survivorship symptoms remains a challenge for researchers. DNA methylation (DNAm) measurements reflecting epigenetic changes caused by anti-cancer therapy may provide needed insights. Given lack of consensus describing utilization of DNAm data to predict survivorship issues, a review evaluating the current landscape is warranted. Provide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors. A literature review was conducted including studies if they focused on cohorts of cancer survivors, utilized peripheral blood cell DNAm data, and evaluated the associations of DNAm and survivorship issues. A total of 22 studies were identified, with majority focused on breast (n = 7) or childhood cancer (n = 9) survivors, and half studies included less than 100 patients (n = 11). Survivorship issues evaluated included those related to neurocognition (n = 5), psychiatric health (n = 3), general wellness (n = 9), chronic conditions (n = 5), and treatment specific toxicities (n = 4). Studies evaluated epigenetic age metrics (n = 10) and DNAm levels at individual CpG sites or regions (n = 12) for their associations with survivorship issues in cancer survivors along with relevant confounding factors. Significant associations of measured DNAm in the peripheral blood samples of cancer survivors and survivorship issues were identified. Studies utilizing epigenetic age metrics and differential methylation analysis demonstrated significant associations of DNAm measurements with survivorship burdens. Associations were observed encompassing diverse survivorship outcomes and timeframes relative to anti-cancer therapy initiation. These findings underscore the potential of these measurements as useful biomarkers in survivorship care and research.

Consortium Profile: The Methylation, Imaging and NeuroDevelopment (MIND) Consortium.

Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 15 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 11,299; Npooled neuroimaging = 10,133; Npooled combined = 4,914). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.

Twin-based Mendelian Randomization Analyses Highlight Smoking's Effects on Blood DNA Methylation, with Putative Reverse Causation.

Epigenome-wide association studies (EWAS) aim to identify differentially methylated loci associated with complex traits and disorders. EWAS of cigarette smoking shows some of the most widespread DNA methylation (DNAm) associations in blood. However, traditional EWAS cannot differentiate between causation and confounding, leading to ambiguity in etiological interpretations. Here, we apply an integrated approach combining Mendelian Randomization and twin-based Direction-of-Causation analyses (MR-DoC) to examine causality underlying smoking-associated blood DNAm changes in the Netherlands Twin Register (N=2577). Evidence across models suggests that current smoking's causal effects on DNAm likely drive many of the previous EWAS findings, implicating functional pathways relevant to several adverse health outcomes of smoking, including hemopoiesis, cell- and neuro-development, and immune regulation. Additionally, we find evidence of potential reverse causal influences at some DNAm sites, with 17 of these sites enriched for gene regulatory functional elements in the brain. The top three sites with evidence of DNAm's effects on smoking annotate to genes involved in G protein-coupled receptor signaling (GNG7, RGS3) and innate immune response (SLC15A4), elucidating potential biological risk factors for smoking. This study highlights the utility of integrating genotypic and DNAm measures in twin cohorts to clarify the causal relationships between health behaviors and blood DNAm.

Prenatal opioid exposure and the early life epigenome: results from ECHO

ABSTRACT Background Prenatal opioid exposure has been associated with adverse child health outcomes. Changes to the epigenome provide a plausible mechanism through which effects may be elicited. We investigated whether prenatal opioid exposure was associated with locus-specific changes in umbilical cord blood DNA methylation (DNAm) and gestational epigenetic age. Methods We leveraged data from the Environmental influences on Child Health Outcomes cohort. Prenatal opioid data was obtained from maternal self-report and/or medical record data. DNAm measures were generated from blood biospecimens collected at birth. Linear regression models tested associations between prenatal maternal opioid exposure and epigenetic outcomes in crude and fully adjusted models. Results We tested the association between prenatal opioid exposure and cord blood DNAm at 15 CpG sites in 385 (n = 25 exposed, n = 360 unexposed) individuals from three cohorts. We identified a single CpG site (cg14303187) that was nominally associated with prenatal opioid exposure (p = 0.02, β = −0.012; 95% CI, −0.023 to −0.0012). No significant associations between exposure and gestational epigenetic age were found (n = 716 individuals from eight cohorts; n = 29 exposed, n = 687 unexposed). Conclusions We identified a nominally significant association between prenatal opioid exposure and DNAm at one CpG site. Future studies should continue investigating the effect of this exposure on the epigenome.

Longitudinal analysis of epigenome-wide DNA methylation reveals novel loci associated with BMI change in East Asians.

Obesity is a global public health concern linked to chronic diseases such as cardiovascular disease and type 2 diabetes (T2D). Emerging evidence suggests that epigenetic modifications, particularly DNA methylation, may contribute to obesity. However, the molecular mechanism underlying the longitudinal change of BMI has not been well-explored, especially in East Asian populations. This study performed a longitudinal epigenome-wide association analysis of DNA methylation to uncover novel loci associated with BMI change in 533 individuals across two Chinese cohorts with repeated DNA methylation and BMI measurements over four years. We identified three novel CpG sites (cg14671384, cg25540824, and cg10848724) significantly associated with BMI change. Two of the identified CpG sites were located in regions previously associated with body shape and basal metabolic rate. Annotation of the top 20 BMI change-associated CpGs revealed strong connections to obesity and T2D. Notably, these CpGs exhibited active regulatory roles and located in genes with high expression in the liver and digestive tract, suggesting a potential regulatory pathway from genome to phenotypes of energy metabolism and absorption via DNA methylation. Cross-sectional and longitudinal EWAS comparisons indicated different mechanisms between CpGs related to BMI and BMI change. This study enhances our understanding of the epigenetic dynamics underlying BMI change and emphasizes the value of longitudinal analyses in deciphering the complex interplay between epigenetics and obesity.

#2045 Epigenetic data can predict initial treatment response in nephrotic syndrome

Abstract Background and Aims The majority of children with idiopathic nephrotic syndrome (INS) and adults with Focal Segmental Glomerulosclerosis (FSGS) and Minimal Change Disease (MCD) receive glucocorticoid treatment at diagnosis. Only those with a high likelihood of having monogenic disease or a contraindication to steroids might avoid this treatment. About 10% overall will not respond to steroids and we have no reliable way of prospectively identifying these patients. Therefore, some patients will receive a futile treatment which is accompanied by significant side effects. DNA methylation (DNAm) is an epigenetic mechanism meaning that it can induce stable but reversible changes in gene expression without any change in underlying DNA sequence. DNAm has shown great potential as a treatment stratification tool, for example, DNAm data is used in oncology to identify which patients are likely to benefit from alkylating chemotherapy. We investigated whether DNAm can predict initial response to steroids in children and young adults with nephrotic syndrome. Method Three hundred and seventeen patients with INS were selected from the NephroS and NURTuRE cohorts. All patients were diagnosed with INS ≤ 30 years of age and those who underwent a renal biopsy had a histological diagnosis of either FSGS or MCD. Peripheral blood DNAm measurements were generated using the Illumina MethylationEPIC Beadchip (&amp;gt;850, 000 CpG sites). Clinical data was used to label patients by their initial response to steroids (sensitive, n = 156, or resistant, n = 161). Machine learning models were created to predict steroid response from the DNAm data. Models were generated using elastic net following feature filtering, and model hyperparameters were tuned and performance measured within the context of cross validation. To exclude whether cumulative steroid exposure prior to sample collection had impacted our results, the CpG sites in the final model were compared to those identified in a published study examining steroid exposure and DNAm (4). Results The 317 INS patients had a median age at diagnosis of 5 years (IQR 2-10) and a median time between diagnosis and DNAm sample collection of 4 years (IQR 1-10). The steroid resistant group were made up of patients with known monogenic disease (n = 75, 24%) and those without pathogenic variants (n = 86, 27%). Initial response to steroid treatment could be predicted with 65% accuracy and an area under the curve (AUC) of 0.75, (sensitivity 0.65, specificity of 0.66, see Fig. 1) using DNAm levels at 14 CpG sites. There was no overlap between the 14 CpG sites in our prediction model and those that are known to alter with steroid treatment. Conclusion We have demonstrated that peripheral blood cell DNAm profiles are a promising predictor of steroid response in INS. Further work to incorporate genetic data into the prediction models is underway and external validation of the results in a separate cohort of patients is required.

Abstract LB206: The progression of chromosomal instability and aberrant DNA methylation during colorectal cancer development

Abstract Chromosomal instability (CIN) and aberrant DNA methylation play a pivotal role in the pathogenesis of colorectal cancer (CRC). Mapping both of these cancer hallmarks during the progression of the disease can help identify potential targets for pharmacological intervention and improve the management of CRC metastasis. In a set of 27 patients diagnosed with either high-grade colorectal adenoma or advanced metastatic CRC disease, high-throughput DNA methylation and/or DNA somatic copy number alterations (SCNAs) analyses were performed. Global genome methylation profiles and the most frequent hot-spot regions harboring SCNAs, identified in the patients' DNA, were verified in a validation set of eight CRC patients through whole-exome sequencing, genome-wide DNA methylation measurement, and gene expression profiling.The study is currently ongoing; however, a panel of 29 cancer-relevant genes, amplified in more than 50% of investigated adenoma tissues (such as PTK6, SRC, MALAT1, BRCA2), was identified. Chromosomal loci amplified in primary tumors were highly concordant with those in liver metastases. An increase in CIN was detected in all metastases, representing mostly gains of Chr7q, 8q, 13q, 20q, and the small arm of ChrX, while the lost chromosomal loci included Chr8p, 17p, and the entire Chr18. A gain unique to metastases was located on Chr6 (p25.1-p22.3), encoding the oncogene DEK. All metastases exhibited an increase in hypomethylated and a decrease in hypermethylated CpGs. The gene enrichment analysis of the differently methylated gene promoters showed the olfactory receptors pathway as the most frequently represented (FDR-adjusted P value=1.06E-8), with all the identified promoters (n=120) less methylated in metastases. Taken together, several genomic hot-spot regions with SCNAs, possibly important during the development of adenoma and also during the metastatic process, were identified. Furthermore, a decrease in methylation within promoters of odorant receptors was the most prominent epigenetic alteration occurring in our set of metastases. The study was funded by the Ministry of Health of the Czech Republic (NU22J-03-00028) and GACR 21-27902S. Citation Format: Katerina Saskova, Mattias Landfors, Josef Horak, Katerina Honkova, Kristyna Tomasova, Jana Drabova, Fernanda Schäfer Hackenhaar, Jitka Pavlikova, Ludmila Vodickova, Torbjörn Nilsson, Sanja Farkas, Veronika Vymetalkova, Pavel Vodicka, Sofie Degerman, Michal Kroupa. The progression of chromosomal instability and aberrant DNA methylation during colorectal cancer development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB206.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays

ABSTRACT DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer’s Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.

Abstract 4772: Metabolic phenotype, age acceleration, and obesity-related cancer risk in Women's Health Initiative and Atherosclerosis Risk in Communities cohorts

Abstract Introduction: While normal physiologic aging causes metabolic decline, metabolic dysregulation owing to excess nutrient intake, physical inactivity, and obesity may drive accelerated aging. However, the relationship of accelerated aging with metabolic dysfunction across different levels of BMI (i.e., metabolic obesity phenotype) and whether it may mediate the relationship with obesity-related cancer (ORC) risk is not well established. Methods: To test this hypothesis, we are leveraging existing blood-based DNA methylation (DNAm) data within the Women’s Health Initiative (WHI) and the Atherosclerosis Risk in Communities (ARIC) cohorts. Weight, height and blood pressure were measured by trained technicians in the respective cohorts and fasting blood glucose, triglycerides and HDL cholesterol were quatified by standard clinican assays. Metabolic obesity phenotypes are classified as metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO), and metabolically unhealthy overweight/obese (MUO) when defined by ATP III criteria. Age acceleration was measured as a residual from regressing pan-tissue Horvath’s DNAmAge on chronological age. Results: The mean baseline age was 64 ± 6.6 years and 54 ± 5.7 year among WHI and ARIC participants, respectively and the age acceleration was measured at an mean follow-up time of 16 years from baseline for WHI and 3.5 years from baseline for ARIC cohort. The outcome of interest, ORC incidence was observed among 474 participants of which 387 were women. The median time for cancer diagnosis from baseline was 25 year and from DNAm measurement was 18.6 years. Of the 4341 (70% women) participants included in the analysis, 23.9% were MHNW, 3.2% MUNW, 39% MHO, and 33.5% MUO. A 31.5% of MHNW, 40.4% of MUNW, 28.7% of MHO, and 35.2% of MUO showed age acceleration. MUNW (OR 1.47, 95% CI: 1.03-2.11) and MUO (OR 1.18, 95% CI: 1.00-1.40) individuals at baseline had increased odds of experiencing age acceleration at a follow-up visit. The risk of all ORC combined was significantly elevated among MUO (HR 1.63, 95% CI: 1.27-2.09) compared to MHNW. Age acceleration at the follow-up visit was not significantly associated with ORC risk (HR 0.91, 95% CI: 0.75-1.11). These analyses were not adjusted for confounders. Conclusions: MUNW and MUO individuals had increased odds of age acceleration at a follow-up visit. Furthermore, MUO individuals were at an elevated risk of ORC, compared to individuals with MHNW. Accelerated aging does not appear to mediate this association, as accelerated aging was not associated with ORC. Citation Format: Prasoona Karra, Garnet L. Anderson, Mary C. Playdon, Sheetal Hardikar, Aladdin Shadyab, Kari E. North, Anne E. Justice, Elizabeth A. Platz, Jan Bressler, Anna Prizment, Weihua Guan, Dominique S. Michaud, Eric A. Whitsel, Brock C. Christensen, Lucas A. Salas. Metabolic phenotype, age acceleration, and obesity-related cancer risk in Women's Health Initiative and Atherosclerosis Risk in Communities cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4772.

Strategies to deal with genetic analyzer-specific DNA methylation measurements.

Targeted bisulfite sequencing using single-base extension (SBE)can be used to measure DNA methylation via capillary electrophoresis on genetic analyzers in forensic labs. Several accurate age prediction models have been reported using this method. However, using different genetic analyzers with different software settings can generate different methylation values, leading to significant errors in age prediction. To address this issue, the study proposes and compares four methods as follows: (1) adjusting methylation values using numerous actual body fluid DNA samples, (2) adjusting methylation values using control DNAs with varying methylation ratios, (3) constructing new age prediction models for each genetic analyzer type, and (4) constructing new age prediction models that could be applied to all types of genetic analyzers. To test the methods for adjusting values using actual body fluid DNA samples, previously reported adjusting equations were used for blood/saliva DNA age prediction markers (ELOVL2, FHL2, KLF14, MIR29B2CHG/C1orf132, and TRIM59). New equations were generated for semen DNA age prediction markers (TTC7B, LOC401324/cg12837463, and LOC729960/NOX4) by drawing polynomial regression lines between the results of the three types of genetic analyzers (3130, 3500, and SeqStudio). The same method was applied to obtain adjustment equations using 11 control DNA samples. To develop new age prediction models for each genetic analyzer type, linear regression analysis was conducted using DNA methylation data from 150 blood, 150 saliva, and 62 semen samples. For the genetic analyzer-independent models, control DNAs were used to formulate equations for calibrating the bias of the data from each genetic analyzer, and linear regression analysis was performed using calibrated body fluid DNA data. In the comparison results, the genetic analyzer-specific models showed the highest accuracy. However, genetic analyzer-independent models through bias adjustment also provided accurate age prediction results, suggesting its use as an alternative in situations with multiple constraints.