DNA Methylation in Whole Blood: Uses and Challenges

Xiaoyao Pills, a Chinese patent medicine, treats mild and moderate depression: A randomized clinical trial combined with DNA methylation analysis

BACKGROUND

Xiaoyao pills (XYP) is a commercial Chinese patent medicine used in the treatment of depression. However, the mechanisms underlying its therapeutic effects, as well as the patients who can benefit from XYP, have not been evaluated so far.

OBJECTIVES

To this end, we conducted a double-blinded, random, and placebo-controlled clinical trial of orally administered XYP in patients with depression.

METHODS

The 17-item Hamilton Depression Rating Scale (HAMD-17) scores were recorded at baseline, and every 2 weeks after the start of treatment. To further elucidate the epigenetic mechanism of XYP, we performed mRNA sequencing and genome-wide DNA methylation sequencing using peripheral blood leukocytes of patients and healthy.

RESULTS

XYP effectively alleviated the symptoms in patients with mild or moderate depressive disorders, particularly that of psychomotor retardation. XYP restored aberrant gene expression and DNA methylation patterns associated with depression, and the normalization of DNA methylation correlated with downregulation of several genes. In addition, altered DNA methylation levels in the XYP-treated samples were attributed to increased expression of the DNA methyltransferase DNMT1.

CONCLUSIONS

Our study provides new insights into the epigenetic mechanism underlying depression and the therapeutic effects of XYP, along with an experimental basis for using XYP in the treatment of depression.

TRIAL REGISTRATION INFORMATION

The name of the registry and number: U.S.

CLINICAL TRIALS REGISTRY

The link to the registration: ClinicalTrials.gov ISRCTN12746343 (https://www.isrctn.com/ISRCTN12746343). The name of the trial register is "Efficacy and safety of the Xiaoyao pill for improving the clinical symptoms of stagnation of liver qi (chi) and spleen deficiency". The clinical trial registration number is ISRCTN12746343.

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

INTRODUCTION

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.

OBJECTIVE

Provide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors.

METHODS

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.

RESULTS

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.

DISCUSSION/CONCLUSION

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.

Demographic characteristics and epigenetic biological aging among post-9/11 veterans: Associations of DunedinPACE with sex, race, and age

Measures of epigenetic aging derived from DNA methylation (DNAm) have enabled the assessment of biological aging in new populations and cohorts. In the present study, we used an epigenetic measure of aging, DunedinPACE, to examine rates of aging across demographic groups in a sample of 2,309 United States military veterans from the VISN 6 MIRECC's Post-Deployment Mental Health Study. As assessed by DunedinPACE, female veterans were aging faster than male veterans (β = 0.39, 95 % CI [0.29, 0.48], p < .001), non-Hispanic Black veterans were aging faster than non-Hispanic White veterans (β = 0.58, 95 % CI [0.50, 0.66], p < .001), and older veterans were biologically aging faster than younger veterans (β = 0.21, 95 % CI [0.18, 0.25], p < .001). In secondary analyses, these differences in rates of aging were not explained by a variety of biopsychosocial covariates. In addition, the percentage of European genetic admixture in non-Hispanic Black veterans was not associated with DunedinPACE. Our findings suggest that female and non-Hispanic Black veterans are at greater risk of accelerated aging among post-9/11 veterans. Interventions that slow aging might provide relatively greater benefit among veterans comprising these at-risk groups.

Genome-wide DNA methylation profiles and breast cancer among World Trade Center survivors

Background

Increased incidence of cancer has been reported among World Trade Center (WTC)-exposed persons. Aberrant DNA methylation is a hallmark of cancer development. To date, only a few small studies have investigated the relationship between WTC exposure and DNA methylation. The main objective of this study was to assess the DNA methylation profiles of WTC-exposed community members who remained cancer free and those who developed breast cancer.

Methods

WTC-exposed women were selected from the WTC Environmental Health Center clinic, with peripheral blood collected during routine clinical monitoring visits. The reference group was selected from the NYU Women's Health Study, a prospective cohort study with blood samples collected before 9 November 2001. The Infinium MethylationEPIC array was used for global DNA methylation profiling, with adjustments for cell type composition and other confounders. Annotated probes were used for biological pathway and network analysis.

Results

A total of 64 WTC-exposed (32 cancer free and 32 with breast cancer) and 32 WTC-unexposed (16 cancer free and 16 with prediagnostic breast cancer) participants were included. Hypermethylated cytosine-phosphate-guanine probe sites (defined as β > 0.8) were more common among WTC-exposed versus unexposed participants (14.3% vs. 4.5%, respectively, among the top 5000 cytosine-phosphate-guanine sites). Cancer-related pathways (e.g., human papillomavirus infection, cGMP-PKG) were overrepresented in WTC-exposed groups (breast cancer patients and cancer-free subjects). Compared to the unexposed breast cancer patients, 47 epigenetically dysregulated genes were identified among WTC-exposed breast cancers. These genes formed a network, including Wnt/β-catenin signaling genes WNT4 and TCF7L2, and dysregulation of these genes contributes to cancer immune evasion.

Conclusion

WTC exposure likely impacts DNA methylation and may predispose exposed individuals toward cancer development, possibly through an immune-mediated mechanism.

Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging

The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.

DNA methylation profiles reveal sex-specific associations between gestational exposure to ambient air pollution and placenta cell-type composition in the PRISM cohort study

BACKGROUND

Gestational exposure to ambient air pollution has been associated with adverse health outcomes for mothers and newborns. The placenta is a central regulator of the in utero environment that orchestrates development and postnatal life via fetal programming. Ambient air pollution contaminants can reach the placenta and have been shown to alter bulk placental tissue DNA methylation patterns. Yet the effect of air pollution on placental cell-type composition has not been examined. We aimed to investigate whether the exposure to ambient air pollution during gestation is associated with placental cell types inferred from DNA methylation profiles.

METHODS

We leveraged data from 226 mother-infant pairs in the Programming of Intergenerational Stress Mechanisms (PRISM) longitudinal cohort in the Northeastern US. Daily concentrations of fine particulate matter (PM2.5) at 1 km spatial resolution were estimated from a spatiotemporal model developed with satellite data and linked to womens' addresses during pregnancy and infants' date of birth. The proportions of six cell types [syncytiotrophoblasts, trophoblasts, stromal, endothelial, Hofbauer and nucleated red blood cells (nRBCs)] were derived from placental tissue 450K DNA methylation array. We applied compositional regression to examine overall changes in placenta cell-type composition related to PM2.5 average by pregnancy trimester. We also investigated the association between PM2.5 and individual cell types using beta regression. All analyses were performed in the overall sample and stratified by infant sex adjusted for covariates.

RESULTS

In male infants, first trimester (T1) PM2.5 was associated with changes in placental cell composition (p = 0.03), driven by a decrease [per one PM2.5 interquartile range (IQR)] of 0.037 in the syncytiotrophoblasts proportion (95% confidence interval (CI) [- 0.066, - 0.012]), accompanied by an increase in trophoblasts of 0.033 (95% CI: [0.009, 0.064]). In females, second and third trimester PM2.5 were associated with overall changes in placental cell-type composition (T2: p = 0.040; T3: p = 0.049), with a decrease in the nRBC proportion. Individual cell-type analysis with beta regression showed similar results with an additional association found for third trimester PM2.5 and stromal cells in females (decrease of 0.054, p = 0.024).

CONCLUSION

Gestational exposure to air pollution was associated with placenta cell composition. Further research is needed to corroborate these findings and evaluate their role in PM2.5-related impact in the placenta and consequent fetal programming.

Whole transcriptome analysis in offspring whose fathers were exposed to a developmental insult: a novel avian model

Although the effects of paternal exposure to insults on the offspring received limited attention in the past, it is currently gaining interest especially after understanding the mechanisms which may mediate such exposure effects. In the current study, the well-controlled avian model (Fayoumi) was utilized to investigate the effects of paternal exposure to the developmental insult, chlorpyrifos on the offspring's gene expression via mRNA and small RNA sequencing. Numerous mRNA gene expression changes were detected in the offspring after paternal exposure to the developmental insult, especially in genes related to neurogenesis, learning and memory. qPCR analysis of several genes, that were significantly changed in mRNA sequencing, confirmed the results obtained in mRNA sequencing. On the other hand, small RNA sequencing did not identify significant microRNA genes expression changes in the offspring after paternal exposure to the developmental insult. The effects of the paternal exposure were more pronounced in the female offspring compared to the male offspring. The results identified expression alterations in major genes (some of which were pertinent to the functional changes observed in other forms of early developmental exposure) after paternal insult exposure and provided a direction for future studies involving the most affected genes.

Polymorphisms in Glutathione S-Transferase (GST) Genes Modify the Effect of Exposure to Maternal Smoking Metabolites in Pregnancy and Offspring DNA Methylation

Maternal smoking in pregnancy (MSP) affects the offspring's DNA methylation (DNAm). There is a lack of knowledge regarding individual differences in susceptibility to exposure to MSP. Glutathione S-transferase (GST) genes are involved in protection against harmful oxidants such as those found in cigarette smoke. This study aimed to test whether polymorphisms in GST genes influence the effect of MSP on offspring DNAm. Using data from the Isle of Wight birth cohort, we assessed the association of MSP and offspring DNAm in 493 mother-child dyads (251 male, 242 female) with the effect-modifying role of GST gene polymorphism (at rs506008, rs574344, rs12736389, rs3768490, rs1537234, and rs1695). MSP was assessed by levels of nicotine and its downstream metabolites (cotinine, norcotinine, and hydroxycotinine) in maternal sera. In males, associations of hydroxycotinine with DNAm at cg18473733, cg25949550, cg11647108, and cg01952185 and norcotinine with DNAm at cg09935388 were modified by GST gene polymorphisms (p-values < 0.05). In females, associations of hydroxycotinine with DNAm at cg12160087 and norcotinine with DNAm at cg18473733 were modified by GST gene polymorphisms (p-values < 0.05). Our study emphasizes the role of genetic polymorphism in GST genes in DNAm's susceptibility to MSP.

Implication of DNA methylation during lifestyle mediated weight loss

Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.

Identification of key DNA methylation changes on fasting plasma glucose: a genome-wide DNA methylation analysis in Chinese monozygotic twins

BACKGROUND

Elevated fasting plasma glucose (FPG) levels can increase morbidity and mortality even when it is below the diagnostic threshold of type 2 diabetes mellitus (T2DM). We conducted a genome-wide DNA methylation analysis to detect DNA methylation (DNAm) variants potentially related to FPG in Chinese monozygotic twins.

METHODS

Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing (RRBS), yielding 551,447 raw CpGs. Association between DNAm of single CpG and FPG was tested using a generalized estimation equation. Differentially methylated regions (DMRs) were identified using comb-P approach. ICE FALCON method was utilized to perform the causal inference. Candidate CpGs were quantified and validated using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data from twins.

RESULTS

The mean age of 52 twin pairs was 52 years (SD: 7). The relationship between DNAm of 142 CpGs and FPG reached the genome-wide significance level. Thirty-two DMRs within 24 genes were identified, including TLCD1, MRPS31P5, CASZ1, and CXADRP3. The causal relationship of top CpGs mapped to TLCD1, MZF1, PTPRN2, SLC6A18, ASTN2, IQCA1, GRIN1, and PDE2A genes with FPG were further identified using ICE FALCON method. Pathways potentially related to FPG were also identified, such as phospholipid-hydroperoxide glutathione peroxidase activity and mitogen-activated protein kinase p38 binding. Three CpGs mapped to SLC6A18 gene were validated in a community population, with a hypermethylated direction in diabetic patients. The expression levels of 18 genes (including SLC6A18 and TLCD1) were positively correlated with FPG levels.

CONCLUSIONS

We detect many DNAm variants that may be associated with FPG in whole blood, particularly the loci within SLC6A18 gene. Our findings provide important reference for the epigenetic regulation of elevated FPG levels and diabetes.

Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data

DNA methylation (DNAm)-based cell mixture deconvolution (CMD) has become a quintessential part of epigenome-wide association studies where DNAm is profiled in heterogeneous tissue types. Despite being introduced over a decade ago, detection limits, which represent the smallest fraction of a cell type in a mixed biospecimen that can be reliably detected, have yet to be determined in the context of DNAm-based CMD. Moreover, there has been little attention given to approaches for quantifying the uncertainty associated with DNAm-based CMD. Here, analytical frameworks for determining both cell-specific limits of detection and quantification of uncertainty associated with DNAm-based CMD are described. This work may contribute to improved rigor, reproducibility and replicability of epigenome-wide association studies involving CMD.

Downregulation of Circulating Hsa-miR-200c-3p Correlates with Dyslipidemia in Patients with Stable Coronary Artery Disease

Coronary heart disease (CHD), one of the leading causes of disability and death worldwide, is a multifactorial disease whose early diagnosis is demanding. Thus, biomarkers predicting the occurrence of this pathology are of great importance from a clinical and therapeutic standpoint. By means of a pilot study on peripheral blood cells (PBMCs) of subjects with no coronary lesions (CTR; n = 2) and patients with stable CAD (CAD; n = 2), we revealed 61 differentially methylated regions (DMRs) (18 promoter regions, 24 genes and 19 CpG islands) and 14.997 differentially methylated single CpG sites (DMCs) in CAD patients. MiRNA-seq results displayed a peculiar miRNAs profile in CAD patients with 18 upregulated and 32 downregulated miRNAs (FC ≥ ±1.5, p ≤ 0.05). An integrated analysis of genome-wide DNA methylation and miRNA-seq results indicated a significant downregulation of hsa-miR-200c-3p (FCCAD = −2.97, p ≤ 0.05) associated to the hypermethylation of two sites (genomic coordinates: chr12:7073122-7073122 and chr12:7072599-7072599) located intragenic to the miR-200c/141 genomic locus (encoding hsa-miR-200c-3p) (p-value = 0.009) in CAD patients. We extended the hsa-miR-200c-3p expression study in a larger cohort (CAD = 72, CTR = 24), confirming its reduced expression level in CAD patients (FCCAD = −2; p = 0.02). However, when we analyzed the methylation status of the two CpG sites in the same cohort, we failed to identify significant differences. A ROC curve analysis showed good performance of hsa-miR-200c-3p expression level (AUC = 0.65; p = 0.02) in distinguishing CAD from CTR. Moreover, we found a significant positive correlation between hsa-miR-200c-3p expression and creatinine clearance (R2 = 0.212, p < 0.005, Pearson r = 0.461) in CAD patients. Finally, a phenotypic correlation performed in the CAD group revealed lower hsa-miR-200c-3p expression levels in CAD patients affected by dyslipidemia (+DLP, n = 58) (p < 0.01). These results indicate hsa-miR-200c-3p as potential epi-biomarker for the diagnosis and clinical progression of CAD and highlight the importance of deeper studies on the expression of this miRNA to understand its functional role in coronary artery disease development.

Probing prenatal bisphenol exposures and tissue-specific DNA methylation responses in cord blood, cord tissue, and placenta

The early-gestational fetal epigenome establishes the landscape for fetal development and is susceptible to disruption via environmental stressors including chemical exposures. Research has explored how cell- and tissue-type-specific epigenomic signatures contribute to human disease, but how the epigenome in each tissue comparatively responds to environmental exposures is largely unknown. This pilot study compared DNA methylation in four previously identified genes across matched cord blood (CB), cord tissue (CT), and placental (PL) samples from 28 mother-infant pairs in tthe Michigan Mother Infant Pairs study; evaluated association between prenatal exposure to bisphenols (BPA, BPF, and BPS) and DNA methylation (DNAm) by tissue type; compared epigenome-wide DNAm of CB and PL; and explored associations between prenatal bisphenol exposures and epigenome-wide DNAm in PL. Bisphenol concentrations were quantified in first-trimester maternal urine. DNAm was assessed at four genes via pyrosequencing in three tissues; epigenome-wide DNAm analysis via Infinium MethylationEPIC array was completed on CB and PL. Candidate gene analysis revealed tissue-specific differences across all genes. In adjusted linear regression, BPA and BPF were associated with DNAm across candidate genes in PL but not CB and CT. Epigenome-wide comparison of matched CB and PL DNAm revealed tissue-specific differences at most CpG sites and modest associations between maternal first-trimester bisphenol exposures and PL but not CB DNAm. These data endorse inclusion of a variety of tissues in prenatal exposure studies. Overlapping and divergent responses in CB, CT, and PL demonstrate their utility in combination to capture a fuller picture of the epigenetic effect of developmental exposures.

Influence of antidepressant drugs on DNA methylation of ion channels genes in blood cells of psychiatric patients

Aim: This study investigated the influence of antidepressant drugs on methylation status of KCNE1, KCNH2 and SCN5A promoters and ECG parameters in adult psychiatric patients. Materials & methods: Electrocardiographic evaluation (24 h) and blood samples were obtained from 34 psychiatric patients before and after 30 days of antidepressant therapy. Methylation of promoter CpG sites of KCNE1, KCNH2 and SCN5A was analyzed by pyrosequencing. Results: Three CpG and four CpG sites of KCNE1 and SCN5A, respectively, had increased % methylation after treatment. Principal component analysis showed correlations of the methylation status with electrocardiographic variables, antidepressant doses and patient age. Conclusion: Short-term treatment with antidepressant drugs increase DNA methylation in KCNE1 and SCN5A promoters, which may induce ECG alterations in psychiatric patients.

Advances in the pathogenesis and clinical application prospects of tumor biomolecules in keloid

Keloid scarring is a kind of pathological healing manifestation after skin injury and possesses various tumor properties, such as the Warburg effect, epithelial-mesenchymal transition (EMT), expression imbalances of apoptosis-related genes and the presence of stem cells. Abnormal expression of tumor signatures is critical to the initiation and operation of these effects. Although previous experimental studies have recognized the potential value of a single or several tumor biomolecules in keloids, a comprehensive evaluation system for multiple tumor signatures in keloid scarring is still lacking. This paper aims to summarize tumor biomolecules in keloids from the perspectives of liquid biopsy, genetics, proteomics and epigenetics and to investigate their mechanisms of action and feasibility from bench to bedside. Liquid biopsy is suitable for the early screening of people with keloids due to its noninvasive and accurate performance. Epigenetic biomarkers do not require changes in the gene sequence and their reversibility and tissue specificity make them ideal therapeutic targets. Nonetheless, given the ethnic specificity and genetic predisposition of keloids, more large-sample multicenter studies are indispensable for determining the prevalence of these signatures and for establishing diagnostic criteria and therapeutic efficacy estimations based on these molecules.

DNA Methylation Analysis of Turner Syndrome BAV

Turner Syndrome (TS) is a rare cytogenetic disorder caused by the complete loss or structural variation of the second sex chromosome. The most common cause of early mortality in TS results from a high incidence of left-sided congenital heart defects, including bicuspid aortic valve (BAV), which occurs in about 30% of individuals with TS. BAV is also the most common congenital heart defect in the general population with a prevalence of 0.5–2%, with males being three-times more likely to have a BAV than females. TS is associated with genome-wide hypomethylation when compared to karyotypically normal males and females. Alterations in DNA methylation in primary aortic tissue are associated with BAV in euploid individuals. Here we show significant differences in DNA methylation patterns associated with BAV in TS found in peripheral blood by comparing TS BAV (n = 12), TS TAV (n = 13), and non-syndromic BAV (n = 6). When comparing TS with BAV to TS with no heart defects we identified a differentially methylated region encompassing the BAV-associated gene MYRF, and enrichment for binding sites of two known transcription factor contributors to BAV. When comparing TS with BAV to euploid women with BAV, we found significant overlapping enrichment for ChIP-seq transcription factor targets including genes in the NOTCH1 pathway, known for involvement in the etiology of non-syndromic BAV, and other genes that are essential regulators of heart valve development. Overall, these findings suggest that altered DNA methylation affecting key aortic valve development genes contributes to the greatly increased risk for BAV in TS.

Upregulation of microRNA-96-5p is associated with adolescent idiopathic scoliosis and low bone mass phenotype

Bone densitometry revealed low bone mass in patients with adolescent idiopathic scoliosis (AIS) and its prognostic potential to predict curve progression. Recent studies showed differential circulating miRNAs in AIS but their diagnostic potential and links to low bone mass have not been well-documented. The present study aimed to compare miRNA profiles in bone tissues collected from AIS and non-scoliotic subjects, and to explore if the selected miRNA candidates could be useful diagnostic biomarkers for AIS. Microarray analysis identified miR-96-5p being the most upregulated among the candidates. miR-96-5p level was measured in plasma samples from 100 AIS and 52 healthy girls. Our results showed significantly higher plasma levels of miR-96-5p in AIS girls with an area under the curve (AUC) of 0.671 for diagnostic accuracy. A model that was composed of plasma miR-96-5p and patient-specific parameters (age, body weight and years since menarche) gave rise to an improved AUC of 0.752. Ingenuity Pathway Analysis (IPA) indicated functional links between bone metabolic pathways and miR-96-5p. In conclusion, differentially expressed miRNAs in AIS bone and plasma samples represented a new source of disease biomarkers and players in AIS etiopathogenesis, which required further validation study involving AIS patients of both genders with long-term follow-up.

Harmonization of transcriptomic and methylomic analysis in environmental epidemiology studies for potential application in chemical risk assessment

Recent efforts have posited the utility of transcriptomic-based approaches to understand chemical-related perturbations in the context of human health risk assessment. Epigenetic modification (e.g., DNA methylation) can influence gene expression changes and is known to occur as a molecular response to some chemical exposures. Characterization of these methylation events is critical to understand the molecular consequences of chemical exposures. In this context, a novel workflow was developed to interrogate publicly available epidemiological transcriptomic and methylomic data to identify relevant pathway level changes in response to chemical exposure, using inorganic arsenic as a case study. Gene Set Enrichment Analysis (GSEA) was used to identify causal methylation events that result in concomitant downstream transcriptional deregulation. This analysis demonstrated an unequal distribution of differentially methylated regions across the human genome. After mapping these events to known genes, significant enrichment of a subset of these pathways suggested that arsenic-mediated methylation may be both specific and non-specific. Parallel GSEA performed on matched transcriptomic samples determined that a substantially reduced subset of these pathways are enriched and that not all chemically-induced methylation results in a downstream alteration in gene expression. The resulting pathways were found to be representative of well-established molecular events known to occur in response to arsenic exposure. The harmonization of enriched transcriptional patterns with those identified from the methylomic platform promoted the characterization of plausibly causal molecular signaling events. The workflow described here enables significant gene and methylation-specific pathways to be identified from whole blood samples of individuals exposed to environmentally relevant chemical levels. As future efforts solidify specific causal relationships between these molecular events and relevant apical endpoints, this novel workflow could aid risk assessments by identifying molecular targets serving as biomarkers of hazard, informing mechanistic understanding, and characterizing dose ranges that promote relevant molecular/epigenetic signaling events occuring in response to chemical exposures.

Social Factors, Epigenomics and Lupus in African American Women (SELA) Study: protocol for an observational mechanistic study examining the interplay of multiple individual and social factors on lupus outcomes in a health disparity population

Introduction

Despite the disproportional impact of SLE on historically marginalised communities, the individual and sociocultural factors underlying these health disparities remain elusive. We report the design and methods for a study aimed at identifying epigenetic biomarkers associated with racism and resiliency that affect gene function and thereby influence SLE in a health disparity population.

Methods and analysis

The Social Factors, Epigenomics and Lupus in African American Women (SELA) Study is a cross-sectional, case–control study. A total of 600 self-reported African American women will be invited to participate. All participants will respond to questionnaires that capture detailed sociodemographic and medical history, validated measures of racial discrimination, social support, as well as disease activity and damage for cases. Participants who wish will receive their genetic ancestry estimates and be involved in research. Blood samples are required to provide peripheral blood mononuclear cell counts, DNA and RNA. The primary goals of SELA are to identify variation in DNA methylation (DNAm) associated with self-reported exposure to racial discrimination and social support, to evaluate whether social DNAm sites affect gene expression, to identify the synergistic effects of social factors on DNAm changes on SLE and to develop a social factors-DNAm predictive model for disease outcomes. This study is conducted in cooperation with the Sea Island Families Project Citizen Advisory Committee.

Discussion and dissemination

SELA will respond to the pressing need to clarify the interplay and regulatory mechanism by which various positive and negative social exposures influence SLE. Results will be published and shared with patients and the community. Knowledge of the biological impact of social exposures on SLE, as informed by the results of this study, can be leveraged by advocacy efforts to develop psychosocial interventions that prevent or mitigate risk exposures, and services or interventions that promote positive exposures. Implementation of such interventions is paramount to the closure of the health disparities gap.

DNA Methylation of Imprinted Genes KCNQ1, KCNQ1OT1, and PHLDA2 in Peripheral Blood Is Associated with the Risk of Breast Cancer

Methylation alterations of imprinted genes lead to loss of imprinting (LOI). Although studies have explored the mechanism of LOI in breast cancer (BC) development, the association between imprinted gene methylation in peripheral blood and BC risk is largely unknown. We utilized HumanMethylation450 data from TCGA and GEO (n = 1461) to identify the CpG sites of imprinted genes associated with BC risk. Furthermore, we conducted an independent case-control study (n = 1048) to validate DNA methylation of these CpG sites in peripheral blood and BC susceptibility. cg26709929, cg08446215, cg25306939, and cg16057921, which are located at KCNQ1, KCNQ1OT1, and PHLDA2, were discovered to be associated with BC risk. Subsequently, the association between cg26709929, cg26057921, and cg25306939 methylation and BC risk was validated in our inhouse dataset. All 22 CpG sites in the KCNQ1OT1 region were associated with BC risk. Individuals with a hypermethylated KCNQ1OT1 region (>0.474) had a lower BC risk (OR: 0.553, 95% CI: 0.397−0.769). Additionally, the methylation of the KCNQ1OT1 region was not significantly different among B cells, monocytes, and T cells, which was also observed at CpG sites in PHLDA2. In summary, the methylation of KCNQ1, KCNQ1OT1, and PHLDA2 was associated with BC risk, and KCNQ1OT1 methylation could be a potential biomarker for BC risk assessment.

Neuronal Dysfunction Is Linked to the Famine-Associated Risk of Proliferative Retinopathy in Patients With Type 2 Diabetes

Persons with type 2 diabetes born in the regions of famine exposures have disproportionally elevated risk of vision-threatening proliferative diabetic retinopathy (PDR) in adulthood. However, the underlying mechanisms are not known. In the present study, we aimed to investigate the plausible molecular factors underlying progression to PDR. To study the association of genetic variants with PDR under the intrauterine famine exposure, we analyzed single nucleotide polymorphisms (SNPs) that were previously reported to be associated with type 2 diabetes, glucose, and pharmacogenetics. Analyses were performed in the population from northern Ukraine with a history of exposure to the Great Ukrainian Holodomor famine [the Diagnostic Optimization and Treatment of Diabetes and its Complications in the Chernihiv Region (DOLCE study), n = 3,583]. A validation of the top genetic findings was performed in the Hong Kong diabetes registry (HKDR, n = 730) with a history of famine as a consequence of the Japanese invasion during WWII. In DOLCE, the genetic risk for PDR was elevated for the variants in ADRA2A, PCSK9, and CYP2C19*2 loci, but reduced at PROX1 locus. The association of ADRA2A loci with the risk of advanced diabetic retinopathy in famine-exposed group was further replicated in HKDR. The exposure of embryonic retinal cells to starvation for glucose, mimicking the perinatal exposure to famine, resulted in sustained increased expression of Adra2a and Pcsk9, but decreased Prox1. The exposure to starvation exhibited a lasting inhibitory effects on neurite outgrowth, as determined by neurite length. In conclusion, a consistent genetic findings on the famine-linked risk of ADRA2A with PDR indicate that the nerves may likely to be responsible for communicating the effects of perinatal exposure to famine on the elevated risk of advanced stages of diabetic retinopathy in adults. These results suggest the possibility of utilizing neuroprotective drugs for the prevention and treatment of PDR.

Investigating the relationship between melatonin patterns and methylation in circadian genes among day shift and night shift workers

OBJECTIVES

Mechanisms underlying the carcinogenicity of night shift work remain uncertain. One compelling yet understudied cancer mechanism may involve altered DNA methylation in circadian genes due to melatonin secretion patterns. The objective of this study was to explore the relationship between melatonin secretion patterns and circadian gene methylation among day and night shift workers.

METHODS

Female healthcare employees (n=38 day workers, n=36 night shift workers) for whom we had urinary 6-sulfatoxymelatonin secretion data from a previous study were recontacted. New blood samples were collected and used to measure methylation levels at 1150 CpG loci across 22 circadian genes using the Illumina Infinium MethylationEPIC beadchip. Linear regression was used to examine the association between melatonin (acrophase and mesor) and M values for each CpG site (false discovery rate, q=0.2), while testing for effect modification by shift work status.

RESULTS

Among night shift workers, a higher mesor (24 hours of mean production of melatonin) was associated with increased methylation in the body of RORA (q=0.02) and decreased methylation in the putative promoter region of MTNR1A (q=0.03). Later acrophase (ie, time of peak concentration) was associated with increased methylation in the putative promoter region of MTNR1A (q=0.20) and decreased methylation in the body of PER3 (q=0.20). No associations were identified among day workers.

CONCLUSIONS

In conclusion, patterns in melatonin secretion were associated with differential circadian gene methylation among night shift workers. Melatonin and alteration of DNA methylation in circadian genes may be one pathway towards increased cancer risk, although larger-scale studies examining multiple time points are needed.

DNA Methylation Analysis of Ribosomal DNA in Adults With Down Syndrome

Control of ribosome biogenesis is a critical aspect of the regulation of cell metabolism. As ribosomal genes (rDNA) are organized in repeated clusters on chromosomes 13, 14, 15, 21, and 22, trisomy of chromosome 21 confers an excess of rDNA copies to persons with Down syndrome (DS). Previous studies showed an alteration of ribosome biogenesis in children with DS, but the epigenetic regulation of rDNA genes has not been investigated in adults with DS so far. In this study, we used a targeted deep-sequencing approach to measure DNA methylation (DNAm) of rDNA units in whole blood from 69 adults with DS and 95 euploid controls. We further evaluated the expression of the precursor of ribosomal RNAs (RNA45S) in peripheral blood mononuclear cells (PBMCs) from the same subjects. We found that the rDNA promoter tends to be hypermethylated in DS concerning the control group. The analysis of epihaplotypes (the combination of methylated and unmethylated CpG sites along the same DNA molecule) showed a significantly lower intra-individual diversity in the DS group, which at the same time was characterized by a higher interindividual variability. Finally, we showed that RNA45S expression is lower in adults with DS. Collectively, our results suggest a rearrangement of the epigenetic profile of rDNA in DS, possibly to compensate for the extranumerary rDNA copies. Future studies should assess whether the regulation of ribosome biogenesis can contribute to the pathogenesis of DS and explain the clinical heterogeneity characteristic of the syndrome.

Mapping the Cord Blood Transcriptome of Pregnancies Affected by Early Maternal Anemia to Identify Signatures of Fetal Programming

CONTEXT

Anemia during early pregnancy (EP) is common in developing countries and is associated with adverse health consequences for both mothers and children. Offspring of women with EP anemia often have low birth weight, which increases risk for cardiometabolic diseases, including type 2 diabetes (T2D), later in life.

OBJECTIVE

We aimed to elucidate mechanisms underlying developmental programming of adult cardiometabolic disease, including epigenetic and transcriptional alterations potentially detectable in umbilical cord blood (UCB) at time of birth.

METHODS

We leveraged global transcriptome- and accompanying epigenome-wide changes in 48 UCB from newborns of EP anemic Tanzanian mothers and 50 controls to identify differentially expressed genes (DEGs) in UCB exposed to maternal EP anemia. DEGs were assessed for association with neonatal anthropometry and cord insulin levels. These genes were further studied in expression data from human fetal pancreas and adult islets to understand their role in beta-cell development and/or function.

RESULTS

The expression of 137 genes was altered in UCB of newborns exposed to maternal EP anemia. These putative signatures of fetal programming, which included the birth weight locus LCORL, were potentially mediated by epigenetic changes in 27 genes and associated with neonatal anthropometry. Among the DEGs were P2RX7, PIK3C2B, and NUMBL, which potentially influence beta-cell development. Insulin levels were lower in EP anemia-exposed UCB, supporting the notion of developmental programming of pancreatic beta-cell dysfunction and subsequently increased risk of T2D in offspring of mothers with EP anemia.

CONCLUSIONS

Our data provide proof-of-concept on distinct transcriptional and epigenetic changes detectable in UCB from newborns exposed to maternal EP anemia.

A Novel Framework for the Identification of Reference DNA Methylation Libraries for Reference-Based Deconvolution of Cellular Mixtures

Reference-based deconvolution methods use reference libraries of cell-specific DNA methylation (DNAm) measurements as a means toward deconvoluting cell proportions in heterogeneous biospecimens (e.g., whole-blood). As the accuracy of such methods depends highly on the CpG loci comprising the reference library, recent research efforts have focused on the selection of libraries to optimize deconvolution accuracy. While existing approaches for library selection work extremely well, the best performing approaches require a training data set consisting of both DNAm profiles over a heterogeneous cell population and gold-standard measurements of cell composition (e.g., flow cytometry) in the same samples. Here, we present a framework for reference library selection without a training dataset (RESET) and benchmark it against the Legacy method (minfi:pickCompProbes), where libraries are constructed based on a pre-specified number of cell-specific differentially methylated loci (DML). RESET uses a modified version of the Dispersion Separability Criteria (DSC) for comparing different libraries and has four main steps: 1) identify a candidate set of cell-specific DMLs, 2) randomly sample DMLs from the candidate set, 3) compute the Modified DSC of the selected DMLs, and 4) update the selection probabilities of DMLs based on their contribution to the Modified DSC. Steps 2–4 are repeated many times and the library with the largest Modified DSC is selected for subsequent reference-based deconvolution. We evaluated RESET using several publicly available datasets consisting of whole-blood DNAm measurements with corresponding measurements of cell composition. We computed the RMSE and R² between the predicted cell proportions and their measured values. RESET outperformed the Legacy approach in selecting libraries that improve the accuracy of deconvolution estimates. Additionally, reference libraries constructed using RESET resulted in cellular composition estimates that explained more variation in DNAm as compared to the Legacy approach when evaluated in the context of epigenome-wide association studies (EWAS) of several publicly available data sets. This finding has implications for the statistical power of EWAS. RESET combats potential challenges associated with existing approaches for reference library assembly and thus, may serve as a viable strategy for library construction in the absence of a training data set.

Association of prenatal acetaminophen use and acetaminophen metabolites with DNA methylation of newborns: analysis of two consecutive generations of the Isle of Wight birth cohort

Acetaminophen is used by nearly two-thirds of pregnant women. Although considered safe, studies have demonstrated associations between prenatal acetaminophen use and adverse health outcomes in offspring. Since DNA methylation (DNAm) at birth may act as an early indicator of later health, assessments on whether DNAm of newborns is associated with gestational acetaminophen use or its metabolites are needed. Using data from three consecutive generations of the Isle of Wight cohort (F0-grandmothers, F1-mothers, and F2-offspring) we investigated associations between acetaminophen metabolites in F0 serum at delivery with epigenome-wide DNAm in F1 (Guthrie cards) and between acetaminophen use of F1 and F2-cord-serum levels with F2 cord blood DNAm. In epigenome-wide screening, we eliminated non-informative DNAm sites followed by linear regression of informative sites. Based on repeated pregnancies, indication bias analyses tested whether acetaminophen indicated maternal diseases or has a risk in its own right. Considering that individuals with similar intake process acetaminophen differently, metabolites were clustered to distinguish metabolic exposures. Finally, metabolite clusters from F1-maternal and F2-cord sera were tested for their associations with newborn DNAm (F1 and F2). Twenty-one differential DNAm sites in cord blood were associated with reported maternal acetaminophen intake in the F2 generation. For 11 of these cytosine-phosphate-guanine (CpG) sites, an indication bias was excluded and five were replicated in F2 with metabolite clusters. In addition, metabolite clusters showed associations with 25 CpGs in the F0-F1 discovery analysis, of which five CpGs were replicated in the F2-generation. Our results suggest that prenatal acetaminophen use, measured as metabolites, may influence DNAm in newborns.

Buffy Coat DNA Methylation Profile Is Representative of Methylation Patterns in White Blood Cell Types in Normal Pregnancy

Background: We aimed to assess the extent to which the buffy coat DNA methylome is representative of methylation patterns in constitutive white blood cell (WBC) types in normal pregnancy. Methods: A comparison of differential methylation of buffy coat DNA vs DNA isolated from polymorphonuclear (PMN) and lymphocytic fractions was performed for each blood sample obtained within 24 h prior to delivery from 29 normotensive pregnant women. Methylation profiles were obtained using an Illumina Human Methylation 450 BeadChip and CHaMP bioinformatics pipeline. A subset of differentially methylated probes (DMPs) showing discordant methylation were further investigated using statistical modeling and enrichment analysis. Results: The smallest number of DMPs was found between the buffy coat and the PMN fraction (2.96%). Pathway enrichment analysis of the DMPs identified biological pathways involved in the particular leukocyte lineage, consistent with perturbations during isolation. The comparisons between the buffy coat and the isolated fractions as a group using linear modeling yielded a small number of probes (∼29,000) with discordant methylation. Demethylation of probes in the buffy coat compared to derived cell lines was more common and was prevalent in shelf and open sea regions. Conclusion: Buffy coat is representative of methylation patterns in WBC types in normal pregnancy. The differential methylations are consistent with perturbations during isolation of constituent cells and likely originate in vitro due to the physical stress during cell separation and are of no physiological relevance. These findings help the interpretation of DNA methylation profiling in pregnancy and numerous other conditions.

Integrating SNPs-based genetic risk factor with blood epigenomic response of differentially arsenic-exposed rural subjects reveals disease-associated signaling pathways

Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals.

DNA Methylation Profiles of Purified Cell Types in Bronchoalveolar Lavage: Applications for Mixed Cell Paediatric Pulmonary Studies

In epigenome-wide association studies analysing DNA methylation from samples containing multiple cell types, it is essential to adjust the analysis for cell type composition. One well established strategy for achieving this is reference-based cell type deconvolution, which relies on knowledge of the DNA methylation profiles of purified constituent cell types. These are then used to estimate the cell type proportions of each sample, which can then be incorporated to adjust the association analysis. Bronchoalveolar lavage is commonly used to sample the lung in clinical practice and contains a mixture of different cell types that can vary in proportion across samples, affecting the overall methylation profile. A current barrier to the use of bronchoalveolar lavage in DNA methylation-based research is the lack of reference DNA methylation profiles for each of the constituent cell types, thus making reference-based cell composition estimation difficult. Herein, we use bronchoalveolar lavage samples collected from children with cystic fibrosis to define DNA methylation profiles for the four most common and clinically relevant cell types: alveolar macrophages, granulocytes, lymphocytes and alveolar epithelial cells. We then demonstrate the use of these methylation profiles in conjunction with an established reference-based methylation deconvolution method to estimate the cell type composition of two different tissue types; a publicly available dataset derived from artificial blood-based cell mixtures and further bronchoalveolar lavage samples. The reference DNA methylation profiles developed in this work can be used for future reference-based cell type composition estimation of bronchoalveolar lavage. This will facilitate the use of this tissue in studies examining the role of DNA methylation in lung health and disease.

Exploring the impact of night shift work on methylation of circadian genes

Night shift work is associated with increased breast cancer risk, but the molecular mechanisms are not well-understood. The objective of this study was to explore the relationship between night shift work parameters (current status, duration/years, and intensity) and methylation in circadian genes as a potential mechanism underlying the carcinogenic effects of night shift work. A cross-sectional study was conducted among 74 female healthcare employees (n = 38 day workers, n = 36 night shift workers). The Illumina Infinium MethylationEPIC beadchip was applied to DNA extracted from blood samples to measure methylation using a candidate gene approach at 1150 CpG loci across 22 circadian genes. Linear regression models were used to examine the association between night shift work parameters and continuous methylation measurements (β-values) for each CpG site. The false-discovery rate (q = 0.2) was used to account for multiple comparisons. Compared to day workers, current night shift workers demonstrated hypermethylation in the 5'UTR region of CSNK1E (q = 0.15). Individuals that worked night shifts for ≥10 years exhibited hypomethylation in the gene body of NR1D1 (q = 0.08) compared to those that worked <10 years. Hypermethylation in the gene body of ARNTL was also apparent in those who worked ≥3 consecutive night shifts a week (q = 0.18). These findings suggest that night shift work is associated with differential methylation in core circadian genes, including CSNK1E, NR1D1 and ARNTL. Future, larger-scale studies with long-term follow-up and detailed night shift work assessment are needed to confirm and expand on these findings.

A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.

DNA Methylation and Type 2 Diabetes: Novel Biomarkers for Risk Assessment?

Diabetes is a severe threat to global health. Almost 500 million people live with diabetes worldwide. Most of them have type 2 diabetes (T2D). T2D patients are at risk of developing severe and life-threatening complications, leading to an increased need for medical care and reduced quality of life. Improved care for people with T2D is essential. Actions aiming at identifying undiagnosed diabetes and at preventing diabetes in those at high risk are needed as well. To this end, biomarker discovery and validation of risk assessment for T2D are critical. Alterations of DNA methylation have recently helped to better understand T2D pathophysiology by explaining differences among endophenotypes of diabetic patients in tissues. Recent evidence further suggests that variations of DNA methylation might contribute to the risk of T2D even more significantly than genetic variability and might represent a valuable tool to predict T2D risk. In this review, we focus on recent information on the contribution of DNA methylation to the risk and the pathogenesis of T2D. We discuss the limitations of these studies and provide evidence supporting the potential for clinical application of DNA methylation marks to predict the risk and progression of T2D.

DNA Methylation Changes Associated With Type 2 Diabetes and Diabetic Kidney Disease in an East Asian Population

CONTEXT

There is a growing body of evidence that epigenetic changes including DNA methylation influence the risk of type 2 diabetes (T2D) and its microvascular complications.

OBJECTIVE

We conducted a methylome-wide association study (MWAS) to identify differentially methylated sites (DMSs) of T2D and diabetic kidney disease (DKD) in a Korean population.

METHODS

We performed an MWAS in 232 participants with T2D and 197 nondiabetic controls with the Illumina EPIC bead chip using peripheral blood leukocytes. The T2D group was subdivided into 87 DKD patients and 80 non-DKD controls. An additional 819 individuals from 2 population-based cohorts were used to investigate the association of identified DMSs with quantitative metabolic phenotypes. A mendelian randomization (MR) approach was applied to evaluate the causal effect of metabolic phenotypes on identified DMSs.

RESULTS

We identified 8 DMSs (each at BMP8A, NBPF20, STX18, ZNF365, CPT1A, and TRIM37, and 2 at TXNIP) that were significantly associated with the risk of T2D (P < 9.0 × 10-8), including 3 that were previously known (DMSs in TXNIP and CPT1A). We also identified 3 DMSs (in COMMD1, TMOD1, and FHOD1) associated with DKD. With our limited sample size, we were not able to observe a significant overlap between DMSs of T2D and DKD. DMSs in TXNIP and CTP1A were associated with fasting glucose and glycated hemoglobin A1c. In MR analysis, fasting glucose was causally associated with DMS in CPT1A.

CONCLUSION

In an East Asian population, we identified 8 DMSs, including 5 novel CpG loci, associated with T2D and 3 DMSs associated with DKD at methylome-wide statistical significance.

Disease-related blood-based differential methylation in cystic fibrosis and its representation in lung cancer revealed a regulatory locus in PKP3 in lung epithelial cells

Cystic fibrosis (CF) is a monogenic disease, characterized by massive chronic lung inflammation. The observed variability in clinical phenotypes in monozygotic CF twins is likely associated with the extent of inflammation. This study sought to investigate inflammation-related aberrant DNA methylation in CF twins and to determine to what extent acquired methylation changes may be associated with lung cancer.

Blood-based genome-wide DNA methylation analysis was performed to compare the DNA methylomes of monozygotic twins, from the European CF Twin and Sibling Study with various degrees of disease severity. Putatively inflammation-related and differentially methylated positions were selected from a large lung cancer case-control study and investigated in blood by targeted bisulphite next-generation-sequencing. An inflammation-related locus located in the Plakophilin-3 (PKP3) gene was functionally analysed regarding promoter and enhancer activity in presence and absence of methylation using luciferase reporter assays.

We confirmed in a unique cohort that monozygotic twins, even if clinically discordant, have only minor differences in global DNA methylation patterns and blood cell composition. Further, we determined the most differentially methylated positions, a high proportion of which are blood cell-type-specific, whereas others may be acquired and thus have potential relevance in the context of inflammation as lung cancer risk factors. We identified a sequence in the gene body of PKP3 which is hypermethylated in blood from CF twins with severe phenotype and highly variably methylated in lung cancer patients and controls, independent of known clinical parameters, and showed that this region exhibits methylation-dependent promoter activity in lung epithelial cells.

Whole-Genome Differentially Hydroxymethylated DNA Regions among Twins Discordant for Cardiovascular Death

Epigenetics is a mechanism underlying cardiovascular disease. It is unknown whether DNA hydroxymethylation is prospectively associated with the risk for cardiovascular death independent of germline and common environment. Male twin pairs middle-aged in 1969–1973 and discordant for cardiovascular death through December 31, 2014, were included. Hydroxymethylation was quantified in buffy coat DNA collected in 1986–1987. The 1893 differentially hydroxymethylated regions (DhMRs) were identified after controlling for blood leukocyte subtypes and age among 12 monozygotic (MZ) pairs (Benjamini–Hochberg False Discovery Rate < 0.01), of which the 102 DhMRs were confirmed with directionally consistent log₂-fold changes and p < 0.01 among additional 7 MZ pairs. These signature 102 DhMRs, independent of the germline, were located on all chromosomes except for chromosome 21 and the Y chromosome, mainly within/overlapped with intergenic regions and introns, and predominantly hyper-hydroxymethylated. A binary linear classifier predicting cardiovascular death among 19 dizygotic pairs was identified and equivalent to that generated from MZ via the 2D transformation. Computational bioinformatics discovered pathways, phenotypes, and DNA motifs for these DhMRs or their subtypes, suggesting that hydroxymethylation was a pathophysiological mechanism underlying cardiovascular death that might be influenced by genetic factors and warranted further investigations of mechanisms of these signature regions in vivo and in vitro.

Current-Smoking alters Gene Expression and DNA Methylation in the Nasal Epithelium of Asthmatics

Current-smoking contributes to worsened asthma prognosis, more severe symptoms and limits the beneficial effects of corticosteroids. As the nasal epithelium can reflect smoking-induced changes in the lower airways, it is a relevant source to investigate changes in gene expression and DNA methylation. This study explores gene expression and DNA methylation changes in current and ex-smokers with asthma. Matched gene expression and epigenome-wide DNA methylation samples collected from nasal brushings of 55 patients enrolled in a clinical trial investigation of current and ex-smoker asthma patients were analysed. Differential gene expression and DNA methylation analyses were conducted comparing current- vs ex-smokers. Expression quantitative trait methylation (eQTM) analysis was completed to explore smoking relevant genes by CpG sites that differ between current and ex-smokers. To investigate the relevance of the smoking-associated DNA methylation changes for the lower airways, significant CpG sites were explored in bronchial biopsies from patients who had stopped smoking. 809 genes and 18,814 CpG sites were differentially associated with current-smoking in the nose. The cis-eQTM analysis uncovered 171 CpG sites whose methylation status associated with smoking-related gene expression, including AHRR, ALDH3A1, CYP1A1 and CYP1B1. Methylation status of CpG sites altered by current-smoking reversed with one-year smoking cessation. We confirm current-smoking alters epigenetic patterns and affects gene expression in the nasal epithelium of asthma patients, which is partially reversible in bronhcial biopsies after smoking cessation. We demonstrate the ability to discern molecular changes in the nasal epithelium, presenting this as a tool in future investigations into disease-relevant effects of tobacco smoke.

An altered global DNA methylation status in women with depression

Sparse studies have shown that specific biomarkers of a global DNA methylation status may be related to various mental diseases and states, including: bipolar disorder (BD), anxiety and major depression disorder (MDD). The objective of this study was to analyze potential variation of the above mentioned global methylation status in women with depression. 38 women with a current and clinically confirmed depressive episode suffering from BD type I, type II or MDD and 71 women from the general population and at similar age were recruited for the study. Alu and LINE-1 methylation was assayed with the quantitative methylation-specific PCR technique with TaqMan probes, while the 5-mC and 5-hmC level was determined using the ELISA-based method. Significantly higher levels of 5-mC, Alu and LINE-1 methylation were observed in the women with depression as compared to the controls; while the 5-hmC level revealed to be significantly lower. The BD type I patients presented the highest level of 5-mC of all the women with a depressive episode. 5-mC level in the patients was positively and significantly correlated with the severity of the symptoms of depression. Relationships between Alu or LINE-1 methylation and 5-mC level were statistically significant only in the case of the control women. Alu and LINE-1 methylation do not constitute suitable biomarkers of global DNA methylation in the investigated patients. These findings require confirmation in case-control and prospective epidemiological studies.

Estimands in epigenome-wide association studies

Background

In DNA methylation analyses like epigenome-wide association studies, effects in differentially methylated CpG sites are assessed. Two kinds of outcomes can be used for statistical analysis: Beta-values and M-values. M-values follow a normal distribution and help to detect differentially methylated CpG sites. As biological effect measures, differences of M-values are more or less meaningless. Beta-values are of more interest since they can be interpreted directly as differences in percentage of DNA methylation at a given CpG site, but they have poor statistical properties. Different frameworks are proposed for reporting estimands in DNA methylation analysis, relying on Beta-values, M-values, or both.

Results

We present and discuss four possible approaches of achieving estimands in DNA methylation analysis. In addition, we present the usage of M-values or Beta-values in the context of bioinformatical pipelines, which often demand a predefined outcome. We show the dependencies between the differences in M-values to differences in Beta-values in two data simulations: a analysis with and without confounder effect. Without present confounder effects, M-values can be used for the statistical analysis and Beta-values statistics for the reporting. If confounder effects exist, we demonstrate the deviations and correct the effects by the intercept method. Finally, we demonstrate the theoretical problem on two large human genome-wide DNA methylation datasets to verify the results.

Conclusions

The usage of M-values in the analysis of DNA methylation data will produce effect estimates, which cannot be biologically interpreted. The parallel usage of Beta-value statistics ignores possible confounder effects and can therefore not be recommended. Hence, if the differences in Beta-values are the focus of the study, the intercept method is recommendable. Hyper- or hypomethylated CpG sites must then be carefully evaluated. If an exploratory analysis of possible CpG sites is the aim of the study, M-values can be used for inference.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01083-9.

Prenatal medication exposure and epigenetic outcomes: a systematic literature review and recommendations for prenatal pharmacoepigenetic studies

When used during pregnancy, analgesics and psychotropics pass the placenta to enter the foetal circulation and may induce epigenetic modifications. Where such modifications occur and whether they disrupt normal foetal developme nt, are currently unanswered questions. This field of prenatal pharmacoepigenetics has received increasing attention, with several studies reporting associations between in utero medication exposure and offspring epigenetic outcomes. Nevertheless, no recent systematic review of the literature is available. Therefore, the objectives of this review were to (i) provide an overview of the literature on the association of prenatal exposure to psychotropics a nd analgesics with epigenetic outcomes, and (ii) suggest recommendations for future studies within prenatal pharmacoepigenetics. We performed systematic literature searches in five databases. The eligible studies assessed human prenatal exposure to psychotropics or analgesics, with epigenetic analyses of offspring tissue as an outcome. We identified 18 eligible studies including 4,419 neonates exposed to either antidepressants, antiepileptic drugs, paracetamol, acetylsalicylic acid, or methadone. The epigenetic outcome in all studies was DNA methylation in cord blood, placental tissue or buccal cells. Although most studies found significant differences in DNA methylation upon medication exposure, almost no differences were persistent across studies for similar medications and sequencing methods. The reviewed studies were challenging to compare due to poor transparency in reporting, and heterogeneous methodology, design, genome coverage, and statistical modelling. We propose 10 recommendations for future prenatal pharmacoepigenetic studies considering both epidemiological and epigenetic perspectives. These recommendations may improve the quality, comparability, and clinical relevance of such studies. PROSPERO registration ID: CRD42020166675.

Investigating gene methylation signatures for fetal intolerance prediction

Pregnancy is a complicated and long procedure during one or more offspring development inside a woman. A short period of oxygen shortage after birth is quite normal for most babies and does not threaten their health. However, if babies have to suffer from a long period of oxygen shortage, then this condition is an indication of pathological fetal intolerance, which probably causes their death. The identification of the pathological fetal intolerance from the physical oxygen shortage is one of the important clinical problems in obstetrics for a long time. The clinical syndromes typically manifest five symptoms that indicate that the baby may suffer from fetal intolerance. At present, liquid biopsy combined with high-throughput sequencing or mass spectrum techniques provides a quick approach to detect real-time alteration in the peripheral blood at multiple levels with the rapid development of molecule sequencing technologies. Gene methylation is functionally correlated with gene expression; thus, the combination of gene methylation and expression information would help in screening out the key regulators for the pathogenesis of fetal intolerance. We combined gene methylation and expression features together and screened out the optimal features, including gene expression or methylation signatures, for fetal intolerance prediction for the first time. In addition, we applied various computational methods to construct a comprehensive computational pipeline to identify the potential biomarkers for fetal intolerance dependent on the liquid biopsy samples. We set up qualitative and quantitative computational models for the prediction for fetal intolerance during pregnancy. Moreover, we provided a new prospective for the detailed pathological mechanism of fetal intolerance. This work can provide a solid foundation for further experimental research and contribute to the application of liquid biopsy in antenatal care.

DNA methylation in the adipose tissue and whole blood of Agent Orange-exposed Operation Ranch Hand veterans: a pilot study

BACKGROUND

Between 1962 and 1971, the US Air Force sprayed Agent Orange across Vietnam, exposing many soldiers to this dioxin-containing herbicide. Several negative health outcomes have been linked to Agent Orange exposure, but data is lacking on the effects this chemical has on the genome. Therefore, we sought to characterize the impact of Agent Orange exposure on DNA methylation in the whole blood and adipose tissue of veterans enrolled in the Air Force Health Study (AFHS).

METHODS

We received adipose tissue (n = 37) and whole blood (n = 42) from veterans in the AFHS. Study participants were grouped as having low, moderate, or high TCDD body burden based on their previously measured serum levels of dioxin. DNA methylation was assessed using the Illumina 450 K platform.

RESULTS

Epigenome-wide analysis indicated that there were no FDR-significantly methylated CpGs in either tissue with TCDD burden. However, 3 CpGs in the adipose tissue (contained within SLC9A3, LYNX1, and TNRC18) were marginally significantly (q < 0.1) hypomethylated, and 1 CpG in whole blood (contained within PTPRN2) was marginally significantly (q < 0.1) hypermethylated with high TCDD burden. Analysis for differentially methylated DNA regions yielded SLC9A3, among other regions in adipose tissue, to be significantly differentially methylated with higher TCDD burden. Comparing whole blood data to a study of dioxin exposed adults from Alabama identified a CpG within the gene SMO that was hypomethylated with dioxin exposure in both studies.

CONCLUSION

We found limited evidence of dioxin associated DNA methylation in adipose tissue and whole blood in this pilot study of Vietnam War veterans. Nevertheless, loci in the genes of SLC9A3 in adipose tissue, and PTPRN2 and SMO in whole blood, should be included in future exposure analyses.

Genome-wide DNA methylation profiling is able to identify prefibrotic PMF cases at risk for progression to myelofibrosis

BACKGROUND

Patients suffering from the BCR-ABL1-negative myeloproliferative disease prefibrotic primary myelofibrosis (pre-PMF) have a certain risk for progression to myelofibrosis. Accurate risk estimation for this fibrotic progression is of prognostic importance and clinically relevant. Commonly applied risk scores are based on clinical, cytogenetic, and genetic data but do not include epigenetic modifications. Therefore, we evaluated the assessment of genome-wide DNA methylation patterns for their ability to predict fibrotic progression in PMF patients.

RESULTS

For this purpose, the DNA methylation profile was analyzed genome-wide in a training set of 22 bone marrow trephines from patients with either fibrotic progression (n = 12) or stable disease over several years (n = 10) using the 850 k EPIC array from Illumina. The DNA methylation classifier constructed from this data set was validated in an independently measured test set of additional 11 bone marrow trephines (7 with stable disease, 4 with fibrotic progress). Hierarchical clustering of methylation β-values and linear discriminant classification yielded very good discrimination between both patient groups. By gene ontology analysis, the most differentially methylated CpG sites are primarily associated with genes involved in cell-cell and cell-matrix interactions.

CONCLUSIONS

In conclusion, we could show that genome-wide DNA methylation profiling of bone marrow trephines is feasible under routine diagnostic conditions and, more importantly, is able to predict fibrotic progression in pre-fibrotic primary myelofibrosis with high accuracy.

Cigarette smoke-induced alterations in blood: A review of research on DNA methylation and gene expression

Worldwide, smoking remains a threat to public health, causing preventable diseases and premature mortality. Cigarette smoke is a powerful inducer of DNA methylation and gene expression alterations, which have been associated with negative health consequences. Here, we review the current knowledge on smoking-related changes in DNA methylation and gene expression in human blood samples. We identified 30 studies focused on the association between active smoking, DNA methylation modifications, and gene expression alterations. Overall, we identified 1,758 genes with differentially methylated sites (DMS) and differentially expressed genes (DEG) between smokers and nonsmokers, of which 261 were detected in multiple studies (≥4). The most frequently (≥10 studies) reported genes were AHRR, GPR15, GFI1, and RARA. Functional enrichment analysis of the 261 genes identified the aryl hydrocarbon receptor repressor and T cell pathways (T helpers 1 and 2) as influenced by smoking status. These results highlight specific genes for future mechanistic and translational research that may be associated with cigarette smoke exposure and smoking-related diseases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

PTSD is associated with increased DNA methylation across regions of HLA-DPB1 and SPATC1L

Posttraumatic stress disorder (PTSD) is characterized by intrusive thoughts, avoidance, negative alterations in cognitions and mood, and arousal symptoms that adversely affect mental and physical health. Recent evidence links changes in DNA methylation of CpG cites to PTSD. Since clusters of proximal CpGs share similar methylation signatures, identification of PTSD-associated differentially methylated regions (DMRs) may elucidate the pathways defining differential risk and resilience of PTSD. Here we aimed to identify epigenetic differences associated with PTSD. DNA methylation data profiled from blood samples using the MethylationEPIC BeadChip were used to perform a DMR analysis in 187 PTSD cases and 367 trauma-exposed controls from the Grady Trauma Project (GTP). DMRs were assessed with R package bumphunter. We identified two regions that associate with PTSD after multiple test correction. These regions were in the gene body of HLA-DPB1 and in the promoter of SPATC1L. The DMR in HLA-DPB1 was associated with PTSD in an independent cohort. Both DMRs included CpGs whose methylation associated with nearby sequence variation (meQTL) and that associated with expression of their respective genes (eQTM). This study supports an emerging literature linking PTSD risk to genetic and epigenetic variation in the HLA region.

Estimating cell-type-specific DNA methylation effects in heterogeneous cellular populations

Aim: To develop a method for estimating cell-specific effects in epigenomic association studies in the presence of cell type heterogeneity. Materials & methods: We utilized Monte Carlo Expectation-Maximization algorithm with Metropolis-Hastings sampler to reconstruct the 'missing' cell-specific methylations and to estimate their associations with phenotypes free of confounding by cell type proportions. Results: Simulations showed reliable performance of the method under various settings including when the cell type is rare. Application to a real dataset recapitulated the directly measured cell-specific methylation pattern in whole blood. Conclusion: This work provides a framework to identify important cell groups and account for cell type composition useful for studying the role of epigenetic changes in human traits and diseases.

Nicotine and Its Downstream Metabolites in Maternal and Cord Sera: Biomarkers of Prenatal Smoking Exposure Associated with Offspring DNA Methylation

Nicotine is a major constituent of cigarette smoke. Its primary metabolite in maternal and cord sera, cotinine, is considered a biomarker of prenatal smoking. Nicotine and cotinine half-lives are decreased in pregnancy due to their increased rate of metabolism and conversion to downstream metabolites such as norcotinine and 3-hydroxycotinine. Hence, downstream metabolites of nicotine may provide informative biomarkers of prenatal smoking. In this study of three generations (F0-mothers, F1-offspring who became mothers, and F2-offspring), we present a biochemical assessment of prenatal smoking exposure based on maternal and cord sera levels of nicotine, cotinine, norcotinine, and 3-hydroxycotinine. As potential markers of early effects of prenatal smoking, associations with differential DNA methylation (DNAm) in the F1- and F2-offspring were assessed. All metabolites in maternal and cord sera were associated with self-reported prenatal smoking, except for nicotine. We compared maternal self-report of smoking in pregnancy to biochemical evidence of prenatal smoking exposure. Self-report of F0-mothers of F1 in 1989–1990 had more accuracy identifying prenatal smoking related to maternal metabolites in maternal serum (sensitivity = 94.6%, specificity = 86.9%) compared to self-reports of F1-mothers of F2 (2010–2016) associated with cord serum markers (sensitivity = 66.7%, specificity = 78.8%). Nicotine levels in sera showed no significant association with any DNAm site previously linked to maternal smoking. Its downstream metabolites, however, were associated with DNAm sites located on the MYO1G, AHRR, and GFI1 genes. In conclusion, cotinine, norcotinine, and 3-hydroxycotinine in maternal and cord sera provide informative biomarkers and should be considered when assessing prenatal smoking. The observed association of offspring DNAm with metabolites, except for nicotine, may imply that the toxic effects of prenatal nicotine exposure are exerted by downstream metabolites, rather than nicotine. If differential DNA methylation on the MYO1G, AHRR, and GFI1 genes transmit adverse effects of prenatal nicotine exposure to the child, there is a need to investigate whether preventing changes in DNA methylation by reducing the metabolic rate of nicotine and conversion to harmful metabolites may protect exposed children.

Association of Neighborhood Deprivation With Epigenetic Aging Using 4 Clock Metrics

IMPORTANCE

Neighborhood deprivation is associated with age-related disease, mortality, and reduced life expectancy. However, biological pathways underlying these associations are not well understood.

OBJECTIVE

To evaluate the association between neighborhood deprivation and epigenetic measures of age acceleration and genome-wide methylation.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the Sister Study, a prospective cohort study comprising 50 884 women living in the US and Puerto Rico aged 35 to 74 years at enrollment who had a sister with breast cancer but had not had breast cancer themselves. Cohort enrollment occurred between July 2003 and March 2009. Participants completed a computer-assisted telephone interview on demographic, socioeconomic, lifestyle, and residential factors and provided anthropometric measures and peripheral blood samples at a home examination. DNA methylation data obtained for 2630 non-Hispanic White women selected for a case-cohort study in 2014 were used in this cross-sectional analysis. DNA methylation was measured using the HumanMethylation450 BeadChips in whole blood samples collected at baseline. Data analysis for this study was performed from October 17, 2019, to August 27, 2020.

EXPOSURES

Each participants' primary address was linked to an established index of neighborhood deprivation.

MAIN OUTCOMES AND MEASURES

Epigenetic age was estimated using 4 epigenetic clocks (Horvath, Hannum, PhenoAge, and GrimAge). Age acceleration was determined using residuals from regressing chronologic age on each of the 4 epigenetic age metrics. Linear regression was used to estimate associations between neighborhood deprivation and epigenetic age acceleration as well as DNA methylation at individual cytosine-guanine sites across the genome.

RESULTS

Mean (SD) age of the 2630 participants was 56.9 (8.7) years. Those with the greatest (>75th percentile) vs least (≤25th percentile) neighborhood deprivation had higher epigenetic age acceleration estimated by Hannum (β = 0.23; 95% CI, 0.01-0.45), PhenoAge (β = 0.28; 95% CI, 0.06-.50), and GrimAge (β = 0.37; 95% CI, 0.12-0.62). Increasing US quartiles of neighborhood deprivation exhibited a trend with Hannum, PhenoAge, and GrimAge. For example, GrimAge showed a significant dose-response (P test for trend <.001) as follows: level 2 vs level 1 (β = 0.30; 95% CI, 0.17-0.42), level 3 vs level 1 (β = 0.35; 95% CI, 0.19-0.50), and level 4 vs level 1 (β = 0.37; 95% CI, 0.12-0.62). Neighborhood deprivation was found to be associated with 3 cytosine-phosphate-guanine sites, with 1 of these annotated to a known gene MAOB (P = 9.71 × 10-08).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that residing in a neighborhood with a higher deprivation index appears to be reflected by methylation-based markers of aging.

DNA methylation biomarkers of future health outcomes in children

Biomarkers which predict future health outcomes are key to the goals of precision health. Such biomarkers do not have to be involved in the causal pathway of a disease, and their performance is best assessed using statistical tests of clinical performance and evaluation of net health impact. DNA methylation is the most commonly studied epigenetic process and represents a potential biomarker of future health outcomes. We review 25 studies in non-oncological paediatric conditions where DNA methylation biomarkers of future health outcomes are assessed. Whilst a number of positive findings have been described, the body of evidence is severely limited by issues with outcome measures, tissue-specific samples, accounting for sample cell type heterogeneity, lack of appropriate statistical testing, small effect sizes, limited validation, and no assessment of net health impact. Future studies should concentrate on careful study design to overcome these issues, and integration of DNA methylation data with other 'omic', clinical, and environmental data to generate the most clinically useful biomarkers of paediatric disease.

Reliability and correlation of mixture cell correction in methylomic and transcriptomic blood data

Objectives

The number of DNA methylome and RNA transcriptome studies is growing, but investigators have to consider the cell type composition of tissues used. In blood samples, the data reflect the picture of a mixture of different cells. Specialized algorithms can address the cell-type heterogeneity issue. We tested if these corrections are correlated between two heterogeneous datasets.

Results

We used methylome and transcriptome datasets derived from a cohort of ten individuals whose blood was sampled at two different timepoints. We examined how the cell composition derived from these omics correlated with each other using “CIBERSORT” for the transcriptome and “estimateCellCounts function” in R for the methylome. The correlation coefficients between the two omic datasets ranged from 0.45 to 0.81 but correlations were minimal between two different timepoints. Our results suggest that a posteriori correction of a mixture of cells present in blood samples is reliable. Using an omic dataset to correct a second dataset for relative fractions of cells appears to be applicable, but only when the samples are simultaneously collected. This could be beneficial when there are difficulties to control the cell types in the second dataset, even when the sample size is limited.