Identification of differentially methylated cell types in epigenome-wide association studies

DNA-based cell typing in menstrual effluent identifies cell type variation by sample collection method: toward noninvasive biomarker development for women's health

Menstrual effluent cell profiles have potential as noninvasive biomarkers of female reproductive and gynecological health and disease. We used DNA methylation-based cell type deconvolution (methylation cytometry) to identify cell type profiles in self-collected menstrual effluent. During the second day of their menstrual cycle, healthy participants collected menstrual effluent using a vaginal swab, menstrual cup, and pad. Immune cell proportions were highest in menstrual cup samples, and epithelial cells were highest in swab samples. Our work demonstrates the feasibility and utility of menstrual effluent cell profiling in population-level research using remotely collected samples and DNA methylation.

Epigenetic ageing clocks: statistical methods and emerging computational challenges

Over the past decade, epigenetic clocks have emerged as powerful machine learning tools, not only to estimate chronological and biological age but also to assess the efficacy of anti-ageing, cellular rejuvenation and disease-preventive interventions. However, many computational and statistical challenges remain that limit our understanding, interpretation and application of epigenetic clocks. Here, we review these computational challenges, focusing on interpretation, cell-type heterogeneity and emerging single-cell methods, aiming to provide guidelines for the rigorous construction of interpretable epigenetic clocks at cell-type and single-cell resolution.

DNA methylome biomarkers of rheumatoid arthritis-associated interstitial lung disease reflecting lung fibrosis pathways, an exploratory case-control study

Rheumatoid Arthritis-associated Interstitial Lung Disease (RA-ILD) significantly reduces life quality and survival, necessitating improvements in its understanding and clinical management. We addressed these goals using DNA methylation analysis, which has not been done in RA-ILD samples, by comparing 32 RA patients with ILD diagnosed less than one year before (cases) and 32 matched RA patients without ILD (controls). This analysis identified 6679 differentially methylated positions (DMPs) with Δβ ≥ 2% and FDR < 0.05, and 576 differentially methylated regions in RA-ILD. Some DMPs were near mucin, collagen, and telomere maintenance genes. Also, the most notably enriched gene set (up to padj = 1.9 × 10-38) included genes overexpressed in fibrosis by monocytes and alveolar macrophages. Other significantly enriched gene sets, known to be dysregulated in fibrosis, included the mitotic spindle and the Rho GTPases. Additionally, analysis of transcription factor binding sites around DMPs showed unique enrichment near the liver X receptor element (LXRE), which is associated with fibrosis in multiple tissues. These results were consistent and unaffected by stricter significance thresholds. They indicated that differential DNA methylation may serve as blood biomarkers for RA-ILD including some related to lung fibrosis pathways.

DNA methylation signatures of severe RSV infection in infants: evidence from non-invasive saliva samples

BACKGROUND

Respiratory syncytial virus (RSV) poses significant morbidity and mortality risks in childhood, particularly for previously healthy infants admitted to hospitals lacking predisposing risk factors for severe disease. This study aimed to investigate the role of the host epigenome in RSV infection severity using non-invasive buccal swabs from sixteen hospitalized infants admitted to the hospital for RSV infection. Eight patients had severe symptoms, and eight had mild to moderate symptoms. For DNA methylation analyses, the Illumina EPIC BeadChip was used with DNA isolated from saliva samples. To evaluate the basal DNA methylation level of the identified biomarkers a cohort of healthy control children was used. Furthermore, DNA methylation levels of candidate genes were confirmed by pyrosequencing in both the discovery and validation cohorts of patients with mild to moderate symptoms.

RESULTS

A panel of differentially methylated positions (DMPs) distinguishing severe from mild to moderate symptoms in infants was identified. DMPs were determined using a threshold of an adjusted P-value (false discovery rate, FDR) < 0.01 and an absolute difference in DNA methylation (delta beta) > 0.10. Differentially methylated regions (DMRs) were identified in the ZBTB38 (implicated in asthma and pulmonary disease) and the TRIM6-TRM34 gene region (associated with viral infections). The differential DNA methylation of these genes was validated in an independent replication cohort. A weighted correlation network analysis emphasized the pivotal role of a module with RAB11FIP5 as the hub gene, known for its critical function in regulating viral infections.

CONCLUSIONS

Oral mucosa methylation may play a role in determining the severity of RSV disease in infants.

Cell-type-specific and inflammatory DNA methylation patterns associated with PTSD

BACKGROUND

Epigenetic modifications, including DNA methylation (DNAm), can change in response to traumatic stress exposure, and may help to distinguish between individuals with and without PTSD. Here, we examine the DNAm patterns specific to immune cell types and inflammation in those with PTSD.

METHODS

This study includes 3,277 participants from 11 cohorts participating in the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup. DNAm was assayed from blood with the MethylationEPIC BeadChip. A standardized QC pipeline was applied and used to impute cell composition. Within each cohort, we identified cell-type-specific DNAm patterns associated with PTSD, controlling for sex (if applicable), age, and ancestry. Meta-analyses were performed from summary statistics.

RESULTS

PTSD cases had lower proportions of B cells and NK cells as well as higher proportions of neutrophils when compared to trauma-exposed controls. Overall, we identified 96 PTSD-associated CpGs across six types of immune cells. Most of these differences were identified in B cells, with 95 % exhibiting lower methylation levels in those with PTSD. Interestingly, the PTSD-associated CpGs annotated to a gene in B cells were enriched in a recent GWAS of PTSD (p < 0.0001).

CONCLUSIONS

This study identifies novel PTSD-associated CpGs in individual immune cell types and supports the role of immune dysregulation and inflammation in PTSD.

Epigenomic and proteomic analyses provide insights into early-life immune regulation and asthma development in infants

Infants with severe bronchiolitis (i.e., bronchiolitis requiring hospitalization) face increased risks of respiratory diseases in childhood. We conduct epigenome-wide association studies in a multi-ethnic cohort of these infants. We identify 61 differentially methylated regions in infant blood (<1 year of age) associated with recurrent wheezing by age 3 (170 cases, 318 non-cases) and/or asthma by age 6 (112 cases, 394 non-cases). These differentially methylated regions are enriched in the enhancers of peripheral blood neutrophils. Several differentially methylated regions exhibit interaction with rhinovirus infection and/or specific blood cell types. In the same blood samples, circulating levels of 104 proteins correlate with the differentially methylated regions, and many proteins show phenotypic association with asthma. Through Mendelian randomization, we find causal evidence supporting a protective role of higher plasma ST2 (also known as IL1RL1) protein against asthma. DNA methylation is also associated with ST2 protein level in infant blood. Taken together, our findings suggest the contribution of DNA methylation to asthma development through regulating early-life systemic immune responses.

Epigenetic Changes in Cerebrospinal Fluid and Blood of People With Neurosyphilis

Epigenetic changes within immune cells may contribute to neuroinflammation during bacterial infection, but their role in neurosyphilis (NS) pathogenesis and response has not yet been established. We longitudinally analyzed DNA methylation and RNA expression in cerebrospinal fluid (CSF) cells and peripheral blood mononuclear cells (PBMCs) from 11 participants with laboratory-confirmed NS (CSF Venereal Disease Research Laboratory test positive) and 11 matched controls with syphilis without NS (non-NS). DNA methylation profiles from CSF and PBMCs of participants with NS significantly differed from those of participants with non-NS. Some genes associated with these differentially methylated sites had corresponding RNA expression changes in the CSF (111/1097 [10.1%]), and included genes involved in B cell activation and insulin-response pathways. Despite antibiotic treatment, approximately 80% of CSF methylation changes associated with NS persisted, suggesting that epigenetic scars accompanying NS may persistently affect immunity following infection. Future studies must examine whether these sequelae are clinically meaningful.

High-resolution reconstruction of cell-type specific transcriptional regulatory processes from bulk sequencing samples

Biological systems exhibit remarkable heterogeneity, characterized by intricate interplay among diverse cell types. Resolving the regulatory processes of specific cell types is crucial for delineating developmental mechanisms and disease etiologies. While single-cell sequencing methods such as scRNA-seq and scATAC-seq have revolutionized our understanding of individual cellular functions, adapting bulk genome-wide assays to achieve single-cell resolution of other genomic features remains a significant technical challenge. Here, we introduce Deep-learning-based DEconvolution of Tissue profiles with Accurate Interpretation of Locus-specific Signals (DeepDETAILS), a novel quasi-supervised framework to reconstruct cell-type-specific genomic signals with base-pair precision. DeepDETAILS' core innovation lies in its ability to perform cross-modality deconvolution using scATAC-seq reference libraries for other bulk datasets, benefiting from the affordability and availability of scATAC-seq data. DeepDETAILS enables high-resolution mapping of genomic signals across diverse cell types, with great versatility for various omics datasets, including nascent transcript sequencing (such as PRO-cap and PRO-seq) and ChIP-seq for chromatin modifications. Our results demonstrate that DeepDETAILS significantly outperformed traditional statistical deconvolution methods. Using DeepDETAILS, we developed a comprehensive compendium of high-resolution nascent transcription and histone modification signals across 39 diverse human tissues and 86 distinct cell types. Furthermore, we applied our compendium to fine-map risk variants associated with Primary Sclerosing Cholangitis (PSC), a progressive cholestatic liver disorder, and revealed a potential etiology of the disease. Our tool and compendium provide invaluable insights into cellular complexity, opening new avenues for studying biological processes in various contexts.

Cell-type-specific subtyping of epigenomes improves prognostic stratification of cancer

BACKGROUND

Most molecular classifications of cancer are based on bulk-tissue profiles that measure an average over many distinct cell types. As such, cancer subtypes inferred from transcriptomic or epigenetic data are strongly influenced by cell-type composition and do not necessarily reflect subtypes defined by cell-type-specific cancer-associated alterations, which could lead to suboptimal cancer classifications.

METHODS

To address this problem, we here propose the novel concept of cell-type-specific combinatorial clustering (CELTYC), which aims to group cancer samples by the molecular alterations they display in specific cell types. We illustrate this concept in the context of DNA methylation data of liver and kidney cancer, deriving in each case novel cancer subtypes and assessing their prognostic relevance against current state-of-the-art prognostic models.

RESULTS

In both liver and kidney cancer, we reveal improved cell-type-specific prognostic models, not discoverable using standard methods. In the case of kidney cancer, we show how combinatorial indexing of epithelial and immune-cell clusters define improved prognostic models driven by synergy of high mitotic age and altered cytokine signaling. We validate the improved prognostic models in independent datasets and identify underlying cytokine-immune-cell signatures driving poor outcome.

CONCLUSIONS

In summary, cell-type-specific combinatorial clustering is a valuable strategy to help dissect and improve current prognostic classifications of cancer in terms of the underlying cell-type-specific epigenetic and transcriptomic alterations.

Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations

Intersample cellular heterogeneity (ISCH) is one of the largest contributors to DNA methylation (DNAme) variability. It is imperative to account for ISCH to accurately interpret analysis results in epigenome-wide association studies. We compiled this primer based on the current literature to guide researchers through the process of estimating and accounting for ISCH in DNA methylation studies. This primer outlines the procedure of bioinformatic ISCH prediction, including using reference-based and reference-free algorithms. It then follows with descriptions of several methods to account for ISCH in downstream analyses, including robust linear regression and principal-component-analysis-based adjustments. Finally, we outlined three methods for estimating differential DNAme signals in a cell-type-specific manner. Throughout the primer, we provided statistical and biological justification for our recommendations, as well as R code examples for ease of implementation.

Epigenome-wide analysis reveals potential biomarkers for radiation-induced toxicity risk in prostate cancer

BACKGROUND

Prostate cancer is the second most common cancer globally, with radiation therapy (RT) being a key treatment for clinically localized and locally advanced cases. Given high survival rates, addressing long-term side effects of RT is crucial for preserving quality-of-life. Radiogenomics, the study of genetic variations affecting response to radiation, has primarily focussed on genomic biomarkers, while DNA methylation studies offer insights into RT responses. Although most research has centred on tumours, no epigenome-wide association studies have explored peripheral blood biomarkers of RT-induced toxicities in prostate cancer patients. Identifying such biomarkers could reveal molecular mechanisms underlying RT response and enable personalized treatment.

METHODS

We analysed 105 prostate cancer patients (52 cases and 53 controls). Cases developed grade ≥ 2 genitourinary and/or gastrointestinal late toxicity after 12 months of starting RT, whereas controls did not. An epigenome-wide association study of post-RT toxicities was performed using the Illumina MethylationEPIC BeadChip, adjusting for age and cell type composition. We constructed two methylation risk scores-one using differentially methylated positions (MRSsites) and another using differentially methylated regions (MRSregions)-as well as a Support Vector Machine-based methylation signature (SVMsites). We evaluated RT effects on biological age and stochastic epigenetic mutations within established radiation response pathways. Gene Ontology and pathway enrichment analyses were also performed.

RESULTS

Pre-RT methylation analysis identified 56 differentially methylated positions (adjusted p-value ≤ 0.05), and 6 differentially methylated regions (p-value ≤ 0.05) associated with the genes NTM, ACAP1, IL1RL2, VOOP1, AKR1E2, and an intergenic region on chromosome 13 related to Short/Long Interspersed Nuclear Elements. Both Methylation Risk Scores (MRSsites AUC = 0.87; MRSregions AUC = 0.89) and the 8-CpG Support Vector Machine signature (SVMsites AUC = 0.98) exhibited strong discriminatory accuracy in classifying patients in the discovery cohort. Gene ontology analysis revealed significant enrichment (adjusted p-value ≤ 0.05) of genes involved in DNA repair, inflammatory response, tissue repair, and oxidative stress response pathways.

CONCLUSIONS

Epigenetic biomarkers show potential for predicting severe long-term adverse effects of RT in prostate cancer patients. The identified methylation patterns provide valuable insights into toxicity mechanisms and may aid personalized treatment strategies. However, validation in independent cohorts is essential to confirm their predictive value and clinical applicability.

A systematic evaluation of cell-type-specific differential methylation analysis in bulk tissue

We conducted a systematic assessment of computational models-CellDMC, TCA, HIRE, TOAST, and CeDAR-for detecting cell-type-specific differential methylation CpGs in bulk methylation data profiled using the Illumina DNA Methylation BeadArrays. This assessment was performed through simulations and case studies involving two epigenome-wide association studies (EWAS) on rheumatoid arthritis and major depressive disorder. Our evaluation provided insights into the strengths and limitations of each model. The results revealed that the models varied in performance across different metrics, sample sizes, and computational efficiency. Additionally, we proposed integrating the results from these models using the minimum p-value ($minpv$) and average p-value ($avepv$) approaches. Our findings demonstrated that these aggregation methods significantly improved performance in identifying cell-type-specific differential methylation CpGs.

Sex differences in epigenetic ageing for older people living with HIV

BACKGROUND

HIV-1 infection impacts biological ageing, and epigenetic clocks highlight epigenetic age acceleration in people with HIV. Despite evidence indicating sex differences in clinical, immunological, and virological measures, females have been underrepresented in most HIV epigenetic studies. Hence, we generated a more representative epigenetic dataset to examine sex differences in epigenetic ageing and relationships to clinical phenotypes and proteomics.

METHODS

We calculated first, second, and third-generation epigenetic ages using DNA methylation data in an observational cohort of 52 females and 106 males with HIV age 50 and over. We profiled plasma biomarkers with Olink high-throughput proteomics to test associations with epigenetic age acceleration. Survival was ascertained over 5 years.

FINDINGS

Epigenetic age acceleration measured by three principal-component based chronological epigenetic age clocks (p = 0.0029, 0.021, 0.010) and one epigenetic mortality risk clock was significantly lower in females living with HIV compared to males (p = 0.0011). Additionally, sex was significantly associated with epigenetic biomarker scores for proportion of naïve CD4+ T cells (p = 0.0006), physical fitness including DNAmGait (p = 0.0010), DNAmGrip (p < 0.0001), and DNAmV02 max (p < 0.0001). We found epigenetic age acceleration associated with plasma proteomic markers involved in inflammation, senescence, immune regulation, kidney function, and tissue homoeostasis (p < 0.0001). Higher epigenetic frailty risk scores were associated with lower CD4 T cell counts (p = 0.0072) and lower CD4/CD8 ratio (p = 0.0017). Slower gait (p = 0.0017), greater frailty (p = 0.0074), and history of smoking (p = 0.042) were associated with increased DNAmFitAge. Risk of death was increased in females with PCPhenoAge acceleration over a 5-year timespan compared to men with PCPhenoAge acceleration (p = 0.03).

INTERPRETATION

These results highlight the importance of studying sex-specific differences in epigenetic ageing biomarkers for HIV-related geroscience research.

FUNDING

National Institute on Aging (K23AG072960), National Center for Advancing Translational Sciences (UL1TR000457), National Institute of Mental Health (R21 MH115821).

Longitudinal leucocyte DNA methylation changes in Mesoamerican nephropathy

Mesoamerican nephropathy (MeN) is a leading cause of morbidity and mortality in Central America, yet its aetiology remains unclear. Environmental exposures including heat stress, pesticides, and heavy metals have all been suggested as possible causes or exacerbating factors of the disease, but intermittent and cumulative exposures are difficult to capture using conventional biomonitoring. Locus-specific differential DNA-methylation (DNAm) which is known to occur in association with these environmental exposures can be readily measured in peripheral blood leucocytes, and therefore have the potential to be used as biomarkers of these exposures. In this study, we aimed first to perform a hypothesis-free epigenome-wide association study of MeN to identify disease-specific methylation signatures, and second to explore the association of DNAm changes associated with potentially relevant environmental exposures and MeN onset. Whole-blood epigenome-wide DNAm was analysed from a total of 312 blood samples: 53 incident cases (pre- and post-evidence of disease onset), 61 matched controls and 16 established cases, collected over a 5-year period. Mixed-effect models identified three unique differentially methylated regions that associated with incident kidney injury, two of which lie within the intron of genes (Amphiphysin on chromosome 7, and SLC29A3 chromosome 10), none of which have been previously reported with any other kidney disease. Next, we conducted a hypothesis-driven analysis examining the coefficients of CpG sites reported to be associated with ambient temperature, pesticides, arsenic, cadmium, and chromium. However, none showed an association with MeN disease onset. Therefore, we did not observe previously reported patterns of DNA methylation that might support a role of pesticides, temperature, or the examined metals in causing MeN.

Immune Dysregulation and Cellular Composition in Lichen Sclerosus Revealed by Integrative Epigenetic Analysis with Cell Type Deconvolution

Background

Lichen sclerosus (LS) is a chronic inflammatory disease affecting skin and mucosal tissues, particularly external genitalia, with a risk of cancer. Its etiology is unknown, possibly involving immune dysregulation and inflammation.

Methods

Study used DNA methylation (DNAme) and single-cell RNA sequencing (scRNA-seq) to compare LS with normal skin. A detailed DNAme profile of LS was created, analyzing differentially methylated probes (DMPs) and cell type-specific DMPs. EpiSCORE deconvolution and immune infiltration analyses identified altered cell types in LS. Immunohistochemistry confirmed cellular changes. Enrichment analysis identified significantly altered pathways, and cell communication analysis described interactions among altered cell types in LS.

Results

DNA methylation patterns generally distinguished LS from normal skin, with a few exceptions. Data analysis showed that T cells significantly increased and fibroblasts decreased in LS. Immunohistochemical staining confirmed the changes in T cells. Enrichment analysis of DMPs indicated significant impacts on fibroblast-related processes and key immune pathways. The COLLAGEN signal was the most prominent in the cell communication. The CD99-CD99 interaction was the strongest between T cells and fibroblasts.

Conclusion

Combining DNAme and scRNA-seq data revealed changes in cellular composition and immune pathways in LS, enhancing understanding of its pathogenesis and highlighting potential therapeutic targets and diagnostic markers.

Co-methylation networks associated with cognition and structural brain development during adolescence

Introduction

Typical adolescent neurodevelopment is marked by decreases in grey matter (GM) volume, increases in myelination, measured by fractional anisotropy (FA), and improvement in cognitive performance.

Methods

To understand how epigenetic changes, methylation (DNAm) in particular, may be involved during this phase of development, we studied cognitive assessments, DNAm from saliva, and neuroimaging data from a longitudinal cohort of normally developing adolescents, aged nine to fourteen. We extracted networks of methylation with patterns of correlated change using a weighted gene correlation network analysis (WCGNA). Modules from these analyses, consisting of co-methylation networks, were then used in multivariate analyses with GM, FA, and cognitive measures to assess the nature of their relationships with cognitive improvement and brain development in adolescence.

Results

This longitudinal exploration of co-methylated networks revealed an increase in correlated epigenetic changes as subjects progressed into adolescence. Co-methylation networks enriched for pathways involved in neuronal systems, potassium channels, neurexins and neuroligins were both conserved across time as well as associated with maturation patterns in GM, FA, and cognition.

Discussion

Our research shows that correlated changes in the DNAm of genes in neuronal processes involved in adolescent brain development that were both conserved across time and related to typical cognitive and brain maturation, revealing possible epigenetic mechanisms driving this stage of development.

Cell-type specific epigenetic clocks to quantify biological age at cell-type resolution

The ability to accurately quantify biological age could help monitor and control healthy aging. Epigenetic clocks have emerged as promising tools for estimating biological age, yet they have been developed from heterogeneous bulk tissues, and are thus composites of two aging processes, one reflecting the change of cell-type composition with age and another reflecting the aging of individual cell-types. There is thus a need to dissect and quantify these two components of epigenetic clocks, and to develop epigenetic clocks that can yield biological age estimates at cell-type resolution. Here we demonstrate that in blood and brain, approximately 39% and 12% of an epigenetic clock's accuracy is driven by underlying shifts in lymphocyte and neuronal subsets, respectively. Using brain and liver tissue as prototypes, we build and validate neuron and hepatocyte specific DNA methylation clocks, and demonstrate that these cell-type specific clocks yield improved estimates of chronological age in the corresponding cell and tissue-types. We find that neuron and glia specific clocks display biological age acceleration in Alzheimer's Disease with the effect being strongest for glia in the temporal lobe. Moreover, CpGs from these clocks display a small but significant overlap with the causal DamAge-clock, mapping to key genes implicated in neurodegeneration. The hepatocyte clock is found accelerated in liver under various pathological conditions. In contrast, non-cell-type specific clocks do not display biological age-acceleration, or only do so marginally. In summary, this work highlights the importance of dissecting epigenetic clocks and quantifying biological age at cell-type resolution.

Expanding Upon Genomics in Rare Diseases: Epigenomic Insights

DNA methylation is an essential epigenetic modification that plays a crucial role in regulating gene expression and maintaining genomic stability. With the advancement in sequencing technology, methylation studies have provided valuable insights into the diagnosis of rare diseases through the various identification of episignatures, epivariation, epioutliers, and allele-specific methylation. However, current methylation studies are not without limitations. This mini-review explores the current understanding of DNA methylation in rare diseases, highlighting the key mechanisms and diagnostic potential, and emphasizing the need for advanced methodologies and integrative approaches to enhance the understanding of disease progression and design more personable treatment for patients, given the nature of rare diseases.

Longitudinal Changes in Epigenetic Age Acceleration Across Childhood and Adolescence

Importance

Individuals exposed to discrimination may exhibit greater epigenetic age acceleration (ie, cellular indicators of premature aging) over time, but few studies have examined longitudinal changes in epigenetic age acceleration, the heterogeneity in these changes for diverse groups of youths, and contextual explanations (ie, discrimination) for differences by ethnicity or race.

Objective

To provide a descriptive illustration of changes in epigenetic age acceleration across childhood and adolescence among an ethnically and racially diverse sample of youths.

Design, Setting, and Participants

This cohort study leveraged longitudinal data on a large sample of youths from low-income households in 20 large urban US cities who provided repeated assessments of saliva tissue samples at ages 9 and 15 years for DNA methylation analysis. Of 4898 youths from the Future of Families and Child Well-Being study, an ongoing study that oversampled children born to unmarried parents from 1998 to 2000, 2039 were included in the present analysis, as these youths had salivary DNA methylation data assayed and publicly available. Analyses were conducted from March 2023 to June 2024.

Exposures

Racialized intrusive encounters with police (eg, stop and frisk and racial slurs).

Main Outcomes and Measures

Analyses were conducted to examine longitudinal changes in salivary epigenetic age acceleration over time, whether such changes varied across ethnically and racially diverse groups of youths, and whether police intrusion was associated with variation across ethnic and racial groups.

Results

Among 2039 youths (mean [SD] age at baseline, 9.27 [0.38] years; 1023 [50%] male and 1016 [50%] female; 917 [45%] Black, 430 [21%] Hispanic or Latino, 351 [17%] White, and 341 [17%] other, including multiple races and self-identified other) with salivary epigenetic clocks at 9 and 15 years of age, longitudinal results showed that White youths exhibited less accelerated epigenetic aging over time than did Black and Hispanic or Latino youths and those reporting other or multiple races or ethnicities from ages 9 to 15 years, particularly in the Hannum (B, 1.54; 95% CI, 0.36-2.18), GrimAge (B, 1.31; 95% CI, 0.68-1.97), and DunedinPACE epigenetic clocks (B, 0.27; 95% CI, 0.11-0.44). Across these clocks and the PhenoAge clock, police intrusion was associated with Black youths' more accelerated epigenetic aging (Hannum: B, 0.11; 95% CI, 0.03-0.23; GrimAge: B, 0.09; 95% CI, 0.03-0.18; PhenoAge: B, 0.08; 95% CI, 0.02-0.18; DunedinPACE: B, 0.01; 95% CI, 0.01-0.03).

Conclusions and Relevance

The transition from childhood to adolescence may represent a sensitive developmental period when racism can have long-term deleterious impacts on healthy human development across the life span. Future research should build on the present study and interrogate which social regularities and policies may be perpetuating discrimination against ethnically and racially minoritized adolescents.

Epigenetic age and long-term cancer risk following a stroke

BACKGROUND

The association between increased cancer risk following a cerebrovascular event (CVE) has been previously reported. We hypothesize that biological age (B-age) acceleration is involved in this association. Our study aims to examine B-age as a novel contributing factor to cancer development post-CVE.

METHODS

From our prospective stroke registry (BasicMar), we selected 940 cases with epigenetic data. For this study, we specifically analyzed 648 of these patients who had available data, no prior history of cancer, and a minimum follow-up of 3 months. The primary outcome was cancer incidence. B-age was estimated using DNA methylation data derived from whole blood samples obtained within 24 h of stroke onset, employing various epigenetic clocks (including Hannum, Horvath, PhenoAge, ZhangBLUP, ZhangEN, and the mitotic epiTOC). Extrinsic epigenetic age acceleration (EEAA) was calculated as the residuals from the regression of B-age against chronological age (C-age). For epiTOC, the age-adjusted values were obtained by regressing out the effect of age from the raw epiTOC measurements. Estimated white cell counts were derived from DNA methylation data, and these cell fractions were used to compute the intrinsic epigenetic age acceleration (IEAA). Subsequently, we evaluated the independent association between EEAA, IEAA, and cancer incidence while controlling for potential confounding variables.

RESULTS

Among 648 patients with a median follow-up of 8.15 years, 83 (12.8%) developed cancer. Cox multivariable analyses indicated significant associations between Hannum, Zhang, and epiTOC EEAA and the risk of cancer after CVE. After adjusting for multiple testing and competing risks, EEAA measured by Hannum clock maintained an independent association with cancer risk. Specifically, for each year increase in Hannum's EEAA, we observed a 6.0% increased incidence of cancer (HR 1.06 [1.02-1.10], p value = 0.002).

CONCLUSIONS

Our findings suggest that epigenetic accelerated aging, as indicated by Hannum's EEAA, may play a significant role in the increased cancer risk observed in CVE survivors.

Mex3a promoter hypomethylation can be utilized to diagnose HBV-associated hepatocellular carcinoma: a randomized controlled trial

BACKGROUND

Hepatocellular carcinoma remains a health challenge for humanity. Therefore, there is an urgent need to develop novel biomarkers with high efficiency yet fast ability to meet the requirements of hepatocellular carcinoma treatment.

METHODS

A total of 229 patients with HBV-associated hepatocellular carcinoma (HCC), 298 patients with chronic hepatitis B (CHB), and 96 healthy controls were retrospectively analyzed. Methylation levels of the Mex3a promoter in peripheral blood mononuclear cells (PBMCs) were measured using MethyLight to obtain clinical and laboratory parameters.

RESULTS

The Mex3a promoter methylation level in HCC patients (median: 0.289% and interquartile range: 0.126%-0.590%) was significantly lower than that in CHB patients (median: 0.999%, interquartile range: 0.417%-1.268%, and p < 0.001) and healthy people (median: 2.172%, interquartile range: 1.225%-3.098%, and p < 0.001). The Mex3a mRNA levels in HCC patients (median: 12.198 and interquartile range: 3.112-18.996) were significantly higher than those in CHB patients (median: 1.623 and interquartile range: 0.066-6.000, and p < 0.001) and healthy controls (median: 0.329, interquartile range: 0.031-1.547, and p < 0.001). MethyLight data were expressed as a percentage of the methylated reference (PMR) value. The Mex3a PMR value was negatively correlated with the mRNA expression level (Spearman's R = -0.829 and p < 0.001). The Mex3a PMR value of HCC patients was significantly correlated with age (Spearman's R = 0.113 and p = 0.044), and the mRNA level was significantly correlated with ALT (Spearman's R = 0.132 and p = 0.046). The Mex3a promoter methylation levels and mRNA levels were also independent factors in the development of liver cancer. The Mex3a promoter methylation and mRNA levels were better at distinguishing HCC from CHB than AFP [area under the receiver operating characteristic curve (AUC) for predicting HCC vs. CHB: 0.915 vs. 0.715: p < 0.001]. The combined use of AFP and Mex3a methylation levels and mRNA levels further improved the area under the receiver operating characteristic curve.

CONCLUSION

The presence of Mex3a promoter hypomethylation in hepatocellular carcinoma can be used as a non-invasive biomarker for the early detection of liver cancer.

Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue

Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.

The potential utility of cord blood DNA methylation in pediatric clinical practice

Our understanding of the origins of noncommunicable diseases has evolved over the years with greater consideration given to the lasting influence exposures and experiences during the preconceptional and prenatal periods can have. Research highlights the associations of parental exposures (e.g., diet, obesity, gestational diabetes, lipid profile, toxic exposures and microbiome) with the infant/fetal methylome and suggest associations with infant, child and/or adolescent chronic health outcomes. Thus, epigenetics and specifically cord blood DNA methylation may have utility as biomarkers for disease risk identification and stratification in pediatrics. However, for cord blood DNA methylation analyses to be leveraged as biomarkers of disease risk in pediatric clinical practice, the results must be replicable, validated and clinically meaningful. Challenges and opportunities to this prospect are herein discussed.

HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data

Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits.

Genome-Wide DNA Methylation Profiling Reveals Low Methylation Variability in Moyamoya Disease

Moyamoya disease (MMD) is a chronic cerebrovascular disorder that can lead to stroke and neurological dysfunctions. Given the largely sporadic nature and the role of gene-environment interactions in various diseases, we examined epigenetic modifications in MMD. We performed genome-wide DNA methylation using Illumina 850 K Methylation EPIC BeadChip, in two racially distinct adult female cohorts: a non-Asian cohort (13 MMD patients and 7 healthy controls) and an Asian cohort (14 MMD patients and 3 healthy controls). An additional external cohort with both sexes (females: 5 MMD patients and 5 healthy controls, males: 5 MMD patients and 5 healthy controls) was included for validation. Our findings revealed strikingly low DNA methylation variability between MMD patients and healthy controls, in both MMD female cohorts. In the non-Asian cohort, only 6 probes showed increased variability versus 647 probes that showed decreased variability. Similarly, in the Asian cohort, the MMD group also displayed a reduced methylation variability across all 2845 probes. Subsequent analysis showed that these differentially variable probes are located on genes involved in key biological processes such as methylation and transcription, DNA repair, cytoskeletal remodeling, natural killer cell signaling, cellular growth, and migration. These findings mark the first observation of low methylation variability in any disease, contrasting with the high variability observed in other disorders. This reduced methylation variability in MMD may hinder patients' adaptability to environmental shifts, such as hemodynamic stress, thereby influencing vascular homeostasis and contributing to MMD pathology. These findings offer new insights into the mechanisms of MMD and potential treatment strategies.

Retro-age: A unique epigenetic biomarker of aging captured by DNA methylation states of retroelements

Reactivation of retroelements in the human genome has been linked to aging. However, whether the epigenetic state of specific retroelements can predict chronological age remains unknown. We provide evidence that locus-specific retroelement DNA methylation can be used to create retroelement-based epigenetic clocks that accurately measure chronological age in the immune system, across human tissues, and pan-mammalian species. We also developed a highly accurate retroelement epigenetic clock compatible with EPICv.2.0 data that was constructed from CpGs that did not overlap with existing first- and second-generation epigenetic clocks, suggesting a unique signal for epigenetic clocks not previously captured. We found retroelement-based epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, and responsive to antiretroviral therapy. Our findings highlight the utility of retroelement-based biomarkers of aging and support a renewed emphasis on the role of retroelements in geroscience.

Exploring the complexities of epigenetics in multiple sclerosis: A study involving meta-analysis of DNA methylation profiles, epigenetic drift, and rare epivariations

Background

Multiple sclerosis (MS) is an autoimmune condition characterized by inflammatory and neurodegenerative traits. Recently, DNA methylation has emerged as a promising field of investigation for elucidating dynamics characterizing MS development and progression.

Objectives

This study aimed to comprehensively investigate the role of epigenetics in MS by analyzing the methylation profiles from blood and brain tissues from public datasets.

Methods

Employing a meta-analytical framework for differential methylation analyses, the study extended beyond conventional analyses to explore additional dimensions of epigenetic regulation, including epigenetic drift, age acceleration, and rare epivariations.

Results

Results of the differential methylation analysis were in line with previously reported findings. No significant differences were observed in age acceleration or global epigenetic drift between MS cases and controls. However, upon closer analysis at the gene level, distinctive patterns of epigenetic drift emerged, particularly within genes implicated in neural biological functions.

Conclusions

These findings underscore the role of epigenetic modifications in shaping MS pathology. Furthermore, the study unveiled the exclusive presence of rare epivariations within the MS cases, some of which involved genes previously linked to MS or other autoimmune diseases. This highlights the potential significance of rare genetic aberrations in driving MS susceptibility and progression.

Lung-Kidney Axis in Cystic Fibrosis: Early Urinary Markers of Kidney Injury Correlate with Neutrophil Activation and Worse Lung Function

Background

Adult people with cystic fibrosis (PwCF) have a higher risk of end-stage kidney disease than the general population. The nature and mechanism of kidney disease in CF are unknown. This study quantifies urinary kidney injury markers and examines the hypothesis that neutrophil activation and lung infection are associated with early kidney injury in CF.

Methods

Urinary total protein, albumin, and markers of kidney injury and neutrophil activation, normalized to creatinine, as well as urinary immune cells, were quantified in CF (n = 48) and healthy (n = 33) cohorts. Infection burden and chronicity were defined by sputum culture and serum titers of anti-bacterial antibodies.

Results

PwCF had increased urinary protein levels, consisting of low-molecular-weight tubular injury markers, independent of glomerular filtration rate (eGFR). This finding suggests subclinical renal injury processes. Urinary analysis of the CF cohort identified different associations of urinary injury markers with aminoglycoside exposure, lung function, and neutrophil activation. High urinary KIM-1 levels and increased prevalence of neutrophils among urine immune cells correlated with decreased lung function in PwCF. The relationship between tubular injury and decreased lung function was most prominent in patients harboring chronic Pseudomonas aeruginosa infection.

Conclusions

Increased urinary tubular injury markers in PwCF suggest early subclinical renal injury not readily detected by eGFR. The strong association of high urinary KIM-1 and neutrophils with diminished lung function and high Pseudomonas aeruginosa burden suggests that pulmonary disease may contribute to renal injury in CF.

DNA Methylation signatures underpinning blood neutrophil to lymphocyte ratio during first week of human life

Understanding of newborn immune ontogeny in the first week of life will enable age-appropriate strategies for safeguarding vulnerable newborns against infectious diseases. Here we conducted an observational study exploring the immunological profile of infants longitudinally throughout their first week of life. Our Expanded Program on Immunization - Human Immunology Project Consortium (EPIC-HIPC) studies the epigenetic regulation of systemic immunity using small volumes of peripheral blood samples collected from West African neonates on days of life (DOL) 0, 1, 3, and 7. Genome-wide DNA methylation and single nucleotide polymorphism markers are examined alongside matched transcriptomic and flow cytometric data. Integrative analysis reveals that a core network of transcription factors mediates dynamic shifts in neutrophil-to-lymphocyte ratios (NLR), which are underpinned by cell-type specific methylation patterns in the two cell types. Genetic variants are associated with lower NLRs at birth, and healthy newborns with lower NLRs at birth are more likely to subsequently develop sepsis. These findings provide valuable insights into the early-life determinants of immune system development.

Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies has not yet been performed. To do so, we optimized Targeted Methylation Sequencing protocol (TMS)-which profiles ∼4 million CpG sites-for miniaturization, flexibility, and multispecies use at a cost of ∼$80. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n=55 paired samples) and whole genome bisulfite sequencing (n=6 paired samples). In both cases, we found strong agreement between technologies (R² = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean=77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R² = 0.98). Finally, we applied our protocol to profile age-associated DNA methylation variation in two subsistence-level populations-the Tsimane of lowland Bolivia and the Orang Asli of Peninsular Malaysia-and found age-methylation patterns that were strikingly similar to those reported in high income cohorts, despite known differences in age-health relationships between lifestyle contexts. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

A comprehensive map of the aging blood methylome in humans

BACKGROUND

During aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated positions (DMPs), their contribution to epigenetic age, and the role of cell type heterogeneity remain unclear.

RESULTS

We conduct a comprehensive analysis of > 32,000 human blood methylomes from 56 datasets (age range = 6-101 years). We find a significant proportion of the blood methylome that is differentially methylated with age (48% DMPs; FDR < 0.005) and variably methylated with age (37% VMPs; FDR < 0.005), with considerable overlap between the two groups (59% of DMPs are VMPs). Bivalent and Polycomb regions become increasingly methylated and divergent between individuals, while quiescent regions lose methylation more uniformly. Both chronological and biological clocks, but not pace-of-aging clocks, show a strong enrichment for CpGs undergoing both mean and variance changes during aging. The accumulation of DMPs shifting towards a methylation fraction of 50% drives the increase in entropy, smoothening the epigenetic landscape. However, approximately a quarter of DMPs exhibit anti-entropic effects, opposing this direction of change. While changes in cell type composition minimally affect DMPs, VMPs and entropy measurements are moderately sensitive to such alterations.

CONCLUSION

This study represents the largest investigation to date of genome-wide DNA methylation changes and aging in a single tissue, providing valuable insights into primary molecular changes relevant to chronological and biological aging.

Genome-Wide DNA methylation profile analysis identifies differentially methylated loci associated with personal PM2.5 exposure in adults with asthma

Particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) is a major environmental risk factor for acute asthma exacerbation, and the underlying mechanism is not completely understood. Studies have indicated that DNA methylation is a potential mechanism linking PM2.5 to its health effects. We conducted a panel study involving 24 adult patients with asthma in Beijing,China between 2017 and 2019. PM2.5 and other atmospheric pollutant exposure data were repeatedly measured. Blood samples were collected for genome-wide DNA methylation analysis. A linear mixed-effects (LME) model was conducted to identify differentially methylated probes (DMPs) associated with PM2.5 exposure. After filtering out probes that did not meet the criteria through quality control, 811,001 CpG sites were included in the LME model, and 36 DMPs were strongly associated with personal PM2.5 exposure at false discovery rate (FDR) < 0.05, of which 22 and 14 DMPs negatively and positively correlated with personal PM2.5 exposure, respectively. Functional analysis revealed that DMPs affected smooth muscle cell contraction and development, extracellular matrix synthesis and secretion, T cell activation and differentiation, and inflammatory factor production. This study provides evidence linking personal PM2.5 exposure to genome-wide DNA methylation in adult patients with asthma. Identifying enrichment pathways can provide biological insights into the acute health effects of PM2.5.

Deciphering DNA Methylation in Gestational Diabetes Mellitus: Epigenetic Regulation and Potential Clinical Applications

Gestational diabetes mellitus (GDM) represents a prevalent complication during pregnancy, exerting both short-term and long-term impacts on maternal and offspring health. This review offers a comprehensive outline of DNA methylation modifications observed in various maternal and offspring tissues affected by GDM, emphasizing the intricate interplay between DNA methylation dynamics, gene expression, and the pathogenesis of GDM. Furthermore, it explores the influence of environmental pollutants, maternal nutritional supplementation, and prenatal gut microbiota on GDM development through alterations in DNA methylation profiles. Additionally, this review summarizes recent advancements in DNA methylation-based diagnostics and predictive models in early GDM detection and risk assessment for subsequent type 2 diabetes. These insights contribute significantly to our understanding of the epigenetic mechanisms underlying GDM development, thereby enhancing maternal and fetal health outcomes and advocating further efforts in this field.

DNA Methylation in the Anti-Mullerian Hormone Gene and the Risk of Disease Activity in Multiple Sclerosis

OBJECTIVE

Multiple sclerosis (MS) has a complex pathobiology, with genetic and environmental factors being crucial players. Understanding the mechanisms underlying heterogeneity in disease activity is crucial for tailored treatment. We explored the impact of DNA methylation, a key mechanism in the genetics-environment interplay, on disease activity in MS.

METHODS

Peripheral immune methylome profiling using Illumina Infinium MethylationEPIC BeadChips was conducted on 249 untreated relapsing-remitting MS patients, sampled at the start of disease-modifying treatment (DMT). A differential methylation analysis compared patients with evidence of disease activity (EDA) to those with no evidence of disease activity (NEDA) over 2 years from DMT start. Utilizing causal inference testing (CIT) and Mendelian randomization (MR), we sought to elucidate the relationships between DNA methylation, gene expression, genetic variation, and disease activity.

RESULTS

Four differentially methylated regions (DMRs) were identified between EDA and NEDA. Examining the influence of single nucleotide polymorphisms (SNPs), 923 variants were found to account for the observed differences in the 4 DMRs. Importantly, 3 out of the 923 SNPs, affecting DNA methylation in a DMR linked to the anti-Mullerian hormone (AMH) gene, were associated with disease activity risk in an independent cohort of 1,408 MS patients. CIT and MR demonstrated that DNA methylation in AMH acts as a mediator for the genetic risk of disease activity.

INTERPRETATION

This study uncovered a novel molecular pathway implicating the interaction between DNA methylation and genetic variation in the risk of disease activity in MS, emphasizing the role of sex hormones, particularly the AMH, in MS pathobiology. ANN NEUROL 2024;96:289-301.

Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene expression and differential methylation

BACKGROUND

Changing cell-type proportions can confound studies of differential gene expression or DNA methylation (DNAm) from peripheral blood mononuclear cells (PBMCs). We examined how cell-type proportions derived from the transcriptome versus the methylome (DNAm) influence estimates of differentially expressed genes (DEGs) and differentially methylated positions (DMPs).

METHODS

Transcriptome and DNAm data were obtained from PBMC RNA and DNA of Kenyan children (n = 8) before, during, and 6 weeks following uncomplicated malaria. DEGs and DMPs between time points were detected using cell-type adjusted modeling with Cibersortx or IDOL, respectively.

RESULTS

Most major cell types and principal components had moderate to high correlation between the two deconvolution methods (r = 0.60-0.96). Estimates of cell-type proportions and DEGs or DMPs were largely unaffected by the method, with the greatest discrepancy in the estimation of neutrophils.

CONCLUSION

Variation in cell-type proportions is captured similarly by both transcriptomic and methylome deconvolution methods for most major cell types.

Respiratory infection- and asthma-prone, low vaccine responder children demonstrate distinct mononuclear cell DNA methylation pathways

BACKGROUND

Infants with frequent viral and bacterial respiratory infections exhibit compromised immunity to routine immunizations. They are also more likely to develop chronic respiratory diseases in later childhood. This study investigated the feasibility of epigenetic profiling to reveal endotype-specific molecular pathways with potential for early identification and immuno-modulation. Peripheral blood mononuclear cells from respiratory infection allergy/asthma-prone (IAP) infants and non-infection allergy/asthma prone (NIAP) were retrospectively selected for genome-wide DNA methylation and single nucleotide polymorphism analysis. The IAP infants were enriched for the low vaccine responsiveness (LVR) phenotype (Fisher's exact p-value = 0.02).

RESULTS

An endotype signature of 813 differentially methylated regions (DMRs) comprising 238 lead CpG associations (FDR < 0.05) emerged, implicating pathways related to asthma, mucin production, antigen presentation and inflammasome activation. Allelic variation explained only a minor portion of this signature. Stimulation of mononuclear cells with monophosphoryl lipid A (MPL), a TLR agonist, partially reversed this signature at a subset of CpGs, suggesting the potential for epigenetic remodeling.

CONCLUSIONS

This proof-of-concept study establishes a foundation for precision endotyping of IAP children and highlights the potential for immune modulation strategies using adjuvants for future investigation.

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 is associated with hair trace elements in female adolescents from two vulnerable populations in the Colombian Caribbean

Exposure to trace elements (TEs) influences DNA methylation patterns, which may be associated with disease development. Vulnerable populations, such as adolescents undergoing maturity, are susceptible to the effects of TE exposure. The aim of this study was to analyze the association of hair TE concentration with DNA methylation in a sample from female adolescents living in two communities in the Colombian Caribbean coast. Hair and blood samples were obtained from 45 females, between 13 and 16 years of age. Seventeen TEs were quantified in hair samples. DNA methylation was measured in leukocytes using the Infinium MethylationEPIC BeadChip. Linear models were employed to identify differentially methylated positions (DMPs) adjusting for age, body mass index, mother's education, and cell type composition. Among the tested elements, vanadium, chromium, nickel, copper, zinc, yttrium, tin, and barium were significantly associated with DMPs (false discovery rate < 0.05), registering 225, 1, 2, 184, 1, 209 189, and 104 hits, respectively. Most of the DMPs were positively associated with TEs and located in open sea regions. The greatest number of DMPs was annotated to the HOXA3 and FOXO3 genes, related to regulation of gene expression and oxidative stress, respectively. These findings suggest that DNA methylation may be involved in linking exposure to TEs among female adolescents to downstream health risks.

LABS: linear amplification-based bisulfite sequencing for ultrasensitive cancer detection from cell-free DNA

Methylation-based liquid biopsies show promises in detecting cancer using circulating cell-free DNA; however, current limitations impede clinical application. Most assays necessitate substantial DNA inputs, posing challenges. Additionally, underrepresented tumor DNA fragments may go undetected during exponential amplification steps of traditional sequencing methods. Here, we report linear amplification-based bisulfite sequencing (LABS), enabling linear amplification of bisulfite-treated DNA fragments in a genome-wide, unbiased fashion, detecting cancer abnormalities with sub-nanogram inputs. Applying LABS to 100 patient samples revealed cancer-specific patterns, copy number alterations, and enhanced cancer detection accuracy by identifying tissue-of-origin and immune cell composition.

DNA methylation profiling of labial salivary gland tissues revealed hypomethylation of B-cell-related genes in primary Sjögren's syndrome

The objective of this epigenetic study was to investigate the cellular proportions based on DNA methylation signatures and pathways of differentially methylated genes in labial salivary gland (LSG) tissues of individuals with Sjögren's syndrome (SS). Two methylation array datasets from the Gene Expression Omnibus repository (GSE166373 and GSE110007) were utilized, consisting of 159 LSG tissues from 77 SS cases and 82 non-SS controls. The raw data underwent analysis using the Chip Analysis Methylation Pipeline (ChAMP) in R statistical tool, which identified differential methylation probes and regions. The EpiDISH and minfi packages in R were employed to identify proportions of epithelial cells, fibroblasts, and immune cells, as well as immune cell subsets. The results showed that proportions of immune cells were increased, while proportions of epithelial cells and fibroblasts were significantly decreased in the LSG of individuals with SS compared to non-SS controls. Specifically, proportions of B-cells and CD8 T-cells were increased, while CD4 T-cells, Treg, monocytes, and neutrophils were decreased in the LSG of individuals with SS. Pathway analysis indicated that genes involved in immune responses to Epstein-Barr virus infection were significantly hypomethylated in SS, and gene set enrichment analysis highlighted the hypomethylation of genes involved in the somatic recombination of immune receptors in SS. Additionally, Disease Ontology analysis showed enriched pathways related to multiple myeloma, arthritis, and the human immunodeficiency virus. The study also revealed significant hypomethylation of the WAS gene on chromosome X in LSG tissues of individuals with SS. Overall, the findings suggest an increased proportion of B-cells and genes related to B-cell function, as well as hypomethylation of genes involved in immune responses and immune receptor recombination, in LSG tissues of individuals with SS compared to non-SS controls.

Investigating neonatal health risk variables through cell-type specific methylome-wide association studies

Adverse neonatal outcomes are a prevailing risk factor for both short- and long-term mortality and morbidity in infants. Given the importance of these outcomes, refining their assessment is paramount for improving prevention and care. Here we aim to enhance the assessment of these often correlated and multifaceted neonatal outcomes. To achieve this, we employ factor analysis to identify common and unique effects and further confirm these effects using criterion-related validity testing. This validation leverages methylome-wide profiles from neonatal blood. Specifically, we investigate nine neonatal health risk variables, including gestational age, Apgar score, three indicators of body size, jaundice, birth diagnosis, maternal preeclampsia, and maternal age. The methylomic profiles used for this research capture data from nearly all 28 million methylation sites in human blood, derived from the blood spot collected from 333 neonates, within 72 h post-birth. Our factor analysis revealed two common factors, size factor, that captured the shared effects of weight, head size, height, and gestational age and disease factor capturing the orthogonal shared effects of gestational age, combined with jaundice and birth diagnosis. To minimize false positives in the validation studies, validation was limited to variables with significant cumulative association as estimated through an in-sample replication procedure. This screening resulted in that the two common factors and the unique effects for gestational age, jaundice and Apgar were further investigated with full-scale cell-type specific methylome-wide association analyses. Highly significant, cell-type specific, associations were detected for both common effect factors and for Apgar. Gene Ontology analyses revealed multiple significant biologically relevant terms for the five fully investigated neonatal health risk variables. Given the established links between adverse neonatal outcomes and both immediate and long-term health, the distinct factor effects (representing the common and unique effects of the risk variables) and their biological profiles confirmed in our work, suggest their potential role as clinical biomarkers for assessing health risks and enhancing personalized care.

Identification of cell-specific epigenetic patterns associated with chondroitin sulfate treatment response in an endemic arthritis, Kashin-Beck disease

Aims

To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment.

Methods

Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue.

Results

This study revealed 21,060 hypermethylated and 44,472 hypomethylated DMRs, and 13,194 hypermethylated and 22,448 hypomethylated CpG islands for differential global methylation for chondroitin sulphate treatment response. A total of 12,666 DMR-related genes containing DMRs were identified in their promoter regions, such as CHL1 (false discovery rate (FDR) = 2.11 × 10-11), RIC8A (FDR = 7.05 × 10-4), and SOX12 (FDR = 1.43 × 10-3). Additionally, RIC8A and CHL1 were hypermethylated in responders, while SOX12 was hypomethylated in responders, all showing decreased gene expression. The patterns of cell-specific differential global methylation associated with chondroitin sulphate response were observed. Specifically, we found that DMRs located in TESPA1 and ATP11A exhibited differential DNA methylation between responders and non-responders in granulocytes, monocytes, and B cells.

Conclusion

Our study identified cell-specific changes in DNA methylation associated with chondroitin sulphate response in KBD patients.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors

Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Respiratory Infection- and Asthma-prone, Low Vaccine Responder Children Demonstrate Distinct Mononuclear Cell DNA Methylation Pathways

Background

Infants with frequent viral and bacterial respiratory infections exhibit compromised immunity to routine immunisations. They are also more likely to develop chronic respiratory diseases in later childhood. This study investigated the feasibility of epigenetic profiling to reveal endotype-specific molecular pathways with potential for early identification and immuno-modulation. Peripharal immune cells from respiratory infection allergy/asthma prone (IAP) infants were retrospectively selected for genome-wide DNA methylation and single nucleotide polymorphism analysis. The IAP infants were enriched for the low vaccine responsiveness (LVR) phenotype (Fishers Exact p-value = 0.01).

Results

An endotype signature of 813 differentially methylated regions (DMRs) comprising 238 lead CpG associations (FDR < 0.05) emerged, implicating pathways related to asthma, mucin production, antigen presentation and inflammasome activation. Allelic variation explained only a minor portion of this signature. Stimulation of mononuclear cells with monophosphoryl lipid A (MPLA), a TLR agonist, partially reversing this signature at a subset of CpGs, suggesting the potential for epigenetic remodelling.

Conclusions

This proof-of-concept study establishes a foundation for precision endotyping of IAP children and highlights the potential for immune modulation strategies using adjuvants for furture investigation.

Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene expression and differential methylation

Background

Changing cell-type proportions can confound studies of differential gene expression or DNA methylation (DNAm) from peripheral blood mononuclear cells (PBMCs). We examined how cell-type proportions derived from the transcriptome versus the methylome (DNAm) influence estimates of differentially expressed genes (DEGs) and differentially methylated positions (DMPs).

Methods

Transcriptome and DNAm data were obtained from PBMC RNA and DNA of Kenyan children (n = 8) before, during, and 6 weeks following uncomplicated malaria. DEGs and DMPs between time points were detected using cell-type adjusted modeling with Cibersortx or IDOL, respectively.

Results

Most major cell types and principal components had moderate to high correlation between the two deconvolution methods (r = 0.60-0.96). Estimates of cell-type proportions and DEGs or DMPs were largely unaffected by the method, with the greatest discrepancy in the estimation of neutrophils.

Conclusion

Variation in cell-type proportions is captured similarly by both transcriptomic and methylome deconvolution methods for most major cell types.

DNA methylation fine-tunes pro-and anti-inflammatory signalling pathways in inactive ulcerative colitis tissue biopsies

DNA methylation has been implied to play a role in the immune dysfunction associated with inflammatory bowel disease (IBD) and the disease development of ulcerative colitis (UC). Changes of the DNA methylation and correlated gene expression in patient samples with inactive UC might reveal possible regulatory features important for further treatment options for UC. Targeted bisulfite sequencing and whole transcriptome sequencing were performed on mucosal biopsies from patients with active UC (UC, n = 14), inactive UC (RM, n = 20), and non-IBD patients which served as controls (NN, n = 11). The differentially methylated regions (DMRs) were identified by DMRseq. Correlation analysis was performed between DMRs and their nearest differentially expressed genes (DEGs). Principal component analysis (PCA) was performed based on correlated DMR regulated genes. DMR regulated genes then were functional annotated. Cell-type deconvolutions were performed based on methylation levels. The comparisons revealed a total of 38 methylation-regulated genes in inactive UC that are potentially regulated by DMRs (correlation p value < 0.1). Several methylation-regulated genes could be identified in inactive UC participating in IL-10 and cytokine signalling pathways such as IL1B and STAT3. DNA methylation events in inactive UC seem to be fine-tuned by the balancing pro- and anti- inflammatory pathways to maintain a prevailed healing process to restore dynamic epithelium homeostasis.

Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts

BACKGROUND

Epigenome-wide association studies (EWAS) have identified CpG sites associated with HIV infection in blood cells in bulk, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. In this study, we aim to identify differentially methylated CpG sites for HIV infection in immune cell types: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes.

METHODS

Applying a computational deconvolution method, we performed a cell-type based EWAS for HIV infection in three independent cohorts (Ntotal = 1,382). DNA methylation in blood or in peripheral blood mononuclear cells (PBMCs) was profiled by an array-based method and then deconvoluted by Tensor Composition Analysis (TCA). The TCA-computed CpG methylation in each cell type was first benchmarked by bisulfite DNA methylation capture sequencing in a subset of the samples. Cell-type EWAS of HIV infection was performed in each cohort separately and a meta-EWAS was conducted followed by gene set enrichment analysis.

RESULTS

The meta-analysis unveiled a total of 2,021 cell-type unique significant CpG sites for five inferred cell types. Among these inferred cell-type unique CpG sites, the concordance rate in the three cohorts ranged from 96% to 100% in each cell type. Cell-type level meta-EWAS unveiled distinct patterns of HIV-associated differential CpG methylation, where 74% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of unique HIV-associated CpG sites (N = 1,624) compared to any other cell type. Genes harboring significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CD4+ T-cells: NLRC5, CX3CR1, B cells: IFI44L, NK cells: IL12R, monocytes: IRF7), and in oncogenesis (e.g. CD4+ T-cells: BCL family, PRDM16, monocytes: PRDM16, PDCD1LG2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis that were enriched among interferon-α and -γ, TNF-α, inflammatory response, and apoptotic pathways.

CONCLUSION

Our findings uncovered computationally inferred cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding HIV pathogenesis.