Epigenome-wide association studies for common human diseases

Present progress in biomarker discovery of endometrial cancer by multi-omics approaches

Endometrial cancer (EC), a prevalent and intricate disease, is associated with a poor prognosis among gynecological malignancies. Its incidence rising globally underscores the urgent need for biomarkers detection in both research and clinical settings. Over the past decade, we've witnessed rapid advancements in biological methodologies and techniques. A multitude of omics technologies, encompassing genomic/transcriptomic sequencing and proteomic/metabolomic mass spectrometry, have been extensively employed to analyze both tissue and liquid samples derived from EC patients. The integration of multi-omics data has not only broadened our understanding of the disease but also unearthed valuable biomarkers specific to EC. This review encapsulates the recent progress and future prospects in the application of multi-omics technologies in EC research, emphasizing the potential of multi-omics in uncovering novel biomarkers and enhancing clinical assessments.

The epipliancy journey: Tumor initiation at the mercy of identity crisis and epigenetic drift

Cellular pliancy refers to the unique disposition of different stages of cellular differentiation to transform when exposed to specific oncogenic insults. This concept highlights a strong interconnection between cellular identity and tumorigenesis, and implies overcoming of epigenetic barriers defining cellular states. Emerging evidence suggests that the cell-type-specific response to intrinsic and extrinsic stresses is modulated by accessibility to certain areas of the genome. Understanding the interplay between epigenetic mechanisms, cellular differentiation, and oncogenic insults is crucial for deciphering the complex nature of tumorigenesis and developing targeted therapies. Hence, cellular pliancy relies on a dynamic cooperation between the cellular identity and the cellular context through epigenetic control, including the reactivation of cellular mechanisms, such as epithelial-to-mesenchymal transition (EMT). Such mechanisms and pathways confer plasticity to the cell allowing it to adapt to a hostile environment in a context of tumor initiation, thus changing its cellular identity. Indeed, growing evidence suggests that cancer is a disease of cell identity crisis, whereby differentiated cells lose their defined identity and gain progenitor characteristics. The loss of cell fate commitment is a central feature of tumorigenesis and appears to be a prerequisite for neoplastic transformation. In this context, EMT-inducing transcription factors (EMT-TFs) cooperate with mitogenic oncoproteins to foster malignant transformation. The aberrant activation of EMT-TFs plays an active role in tumor initiation by alleviating key oncosuppressive mechanisms and by endowing cancer cells with stem cell-like properties, including the ability to self-renew, thus changing the course of tumorigenesis. This highly dynamic phenotypic change occurs concomitantly to major epigenome reorganization, a key component of cell differentiation and cancer cell plasticity regulation. The concept of pliancy was initially proposed to address a fundamental question in cancer biology: why are some cells more likely to become cancerous in response to specific oncogenic events at particular developmental stages? We propose the concept of epipliancy, whereby a difference in epigenetic configuration leads to malignant transformation following an oncogenic insult. Here, we present recent studies furthering our understanding of how the epigenetic landscape may impact the modulation of cellular pliancy during early stages of cancer initiation.

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.

The Circulating Methylome in Childhood-Onset Inflammatory Bowel Disease

BACKGROUND

The genetic contribution to inflammatory bowel disease (IBD), encompassing both Crohn's disease (CD) and ulcerative colitis (UC), accounts for around 20% of disease variance, highlighting the need to characterize environmental and epigenetic influences. Recently, considerable progress has been made in characterizing the adult methylome in epigenome-wide association studies.

METHODS

We report detailed analysis of the circulating methylome in 86 patients with childhood-onset CD and UC and 30 controls using the Illumina Infinium Human MethylationEPIC platform.

RESULTS

We derived and validated a 4-probe methylation biomarker (RPS6KA2, VMP1, CFI, and ARHGEF3), with specificity and high diagnostic accuracy for pediatric IBD in UK and North American cohorts (area under the curve: 0.90-0.94). Significant epigenetic age acceleration is present at diagnosis, with the greatest observed in CD patients. Cis-methylation quantitative trait loci (meQTL) analysis identifies genetic determinants underlying epigenetic alterations notably within the HLA 6p22.1-p21.33 region. Passive smoking exposure is associated with the development of UC rather than CD, contrary to previous findings.

CONCLUSIONS

These data provide new insights into epigenetic alterations in IBD and illustrate the reproducibility and translational potential of epigenome-wide association studies in complex diseases.

Gene expression variation across genetically identical individuals predicts reproductive traits

In recent decades, genome-wide association studies (GWAS) have been the major approach to understand the biological basis of individual differences in traits and diseases. However, GWAS approaches have limited predictive power to explain individual differences, particularly for complex traits and diseases in which environmental factors play a substantial role in their etiology. Indeed, individual differences persist even in genetically identical individuals, although fully separating genetic and environmental causation is difficult in most organisms. To understand the basis of individual differences in the absence of genetic differences, we measured two quantitative reproductive traits in 180 genetically identical young adult Caenorhabditis elegans roundworms in a shared environment and performed single-individual transcriptomics on each worm. We identified hundreds of genes for which expression variation was strongly associated with reproductive traits, some of which depended on individuals' historical environments and some of which was random. Multiple small sets of genes together were highly predictive of reproductive traits, explaining on average over half and over a quarter of variation in the two traits. We manipulated mRNA levels of predictive genes to identify a set of causal genes, demonstrating the utility of this approach for both prediction and understanding underlying biology. Finally, we found that the chromatin environment of predictive genes was enriched for H3K27 trimethylation, suggesting that gene expression variation may be driven in part by chromatin structure. Together, this work shows that individual, non-genetic differences in gene expression are both highly predictive and causal in shaping reproductive traits.

Multi-omics in Allergic Rhinitis: Mechanism Dissection and Precision Medicine

Allergic rhinitis (AR) is a common chronic inflammatory airway disease caused by inhaled allergens, and its prevalence has increased in recent decades. AR not only causes nasal leakage, itchy nose, nasal congestion, sneezing, and allergic conjunctivitis but also induces asthma, as well as sleep disorders, anxiety, depression, memory loss, and other phenomena that seriously affect the patient's ability to study and work, lower their quality of life, and burden society. The current methods used to diagnose and treat AR are still far from ideal. Multi-omics technology can be used to comprehensively and systematically analyze the differentially expressed DNA, RNA, proteins, and metabolites and their biological functions in patients with AR. These capabilities allow for an in-depth understanding of the intrinsic pathogenic mechanism of AR, the ability to explore key cells and molecules that drive its progression, and to design personalized treatment for AR. This article summarizes the progress made in studying AR by use of genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics in order to illustrate the important role of multi-omics technologies in facilitating the precise diagnosis and treatment of AR.

Human genomic regions of systemic interindividual epigenetic variation are implicated in neurodevelopmental and metabolic disorders

Epigenome-wide association studies (EWAS) profile DNA methylation across the human genome to identify associations with diseases and exposures. Most employ Illumina methylation arrays; this platform, however, under-samples interindividual epigenetic variation. The systemic and stable nature of epigenetic variation at correlated regions of systemic interindividual variation (CoRSIVs) should be advantageous to EWAS. Here, we analyze 2,203 published EWAS to determine whether Illumina probes within CoRSIVs are over-represented in the literature. Enrichment of CoRSIV-overlapping probes was observed for most classes of disease, particularly for neurodevelopmental disorders and type 2 diabetes, indicating an opportunity to improve the power of EWAS by over 200- and over 100-fold, respectively. EWAS targeting all known CoRSIVs should accelerate discovery of associations between individual epigenetic variation and risk of disease.

Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease

AIM

Diabetes is increasing in prevalence worldwide, with a 20% rise in prevalence predicted between 2021 and 2030, bringing an increased burden of complications, such as diabetic kidney disease (DKD). DKD is a leading cause of end-stage kidney disease, with significant impacts on patients, families and healthcare providers. DKD often goes undetected until later stages, due to asymptomatic disease, non-standard presentation or progression, and sub-optimal screening tools and/or provision. Deeper insights are needed to improve DKD diagnosis, facilitating the identification of higher-risk patients. Improved tools to stratify patients based on disease prognosis would facilitate the optimisation of resources and the individualisation of care. This review aimed to identify how multiomic approaches provide an opportunity to understand the complex underlying biology of DKD.

METHODS

This review explores how multiomic analyses of DKD are improving our understanding of DKD pathology, and aiding in the identification of novel biomarkers to detect disease earlier or predict trajectories.

RESULTS

Effective multiomic data integration allows novel interactions to be uncovered and empathises the need for harmonised studies and the incorporation of additional data types, such as co-morbidity, environmental and demographic data to understand DKD complexity. This will facilitate a better understanding of kidney health inequalities, such as social-, ethnicity- and sex-related differences in DKD risk, onset and progression.

CONCLUSION

Multiomics provides opportunities to uncover how lifetime exposures become molecularly embodied to impact kidney health. Such insights would advance DKD diagnosis and treatment, inform preventative strategies and reduce the global impact of this disease.

Binding of PtoRAP2.12 to demethylated and accessible chromatin regions in the PtoGntK promoter stimulates growth of poplar

DNA methylation is an essential epigenetic modification for gene regulation in plant growth and development. However, the precise mechanisms of DNA methylation remain poorly understood, especially in woody plants. We employed whole-genome bisulfite sequencing (WGBS), assays for transposase-accessible chromatin using sequencing (ATAC-seq), and RNA-Seq to investigate epigenetic regulatory relationships in Populus tomentosa treated with DNA methylation inhibitor 5-azacitidine. Expression-quantitative trait methylation analysis (eQTM), epigenome-wide association study (EWAS), and joint linkage-linkage disequilibrium mapping were used to explore the epigenetic regulatory genes, and using CRISPR/Cas9 to identify the role of candidate genes. Plant developmental abnormalities occurred when DNA methylation levels were substantially reduced. DNA methylation regulated 112 expressed genes via chromatin accessibility, of which 61 genes were significantly influenced by DNA methylation variation at the population level. One DNA methylation-regulated gene, PtoGntK, was located in a major quantitative trait locus (QTL) for poplar growth. Overexpression and CRISPR/Cas9 of PtoGntK revealed it affected poplar height and stem diameter. The PtoRAP2.12 was found to bind to the demethylated accessible region in the PtoGntK promoter, thereby promoting growth in poplar. This study identified key genes with epigenetic regulation for plant growth and provides insights into epigenetic regulation mechanisms in woody plants.

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

A General Framework for the Multiple Nonparametric Behrens-Fisher Problem With Dependent Replicates

In many trials and experiments, subjects are not only observed once but multiple times, resulting in a cluster of possibly correlated observations (e.g., brain regions per patient). Observations often do not fulfill model assumptions of mixed models and require the use of nonparametric methods. In this article, we develop and present a purely nonparametric rank-based procedure that flexibly allows the unbiased and consistent estimation of the Wilcoxon-Mann-Whitney effectP ( X < Y ) + 1 2 P ( X = Y ) $$ P\left(X Collapse

Key Words

• Behrens–Fisher
• cluster
• multiple testing
• nonparametric
• replicates

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MESH Headings

• Statistics, Nonparametric
• Humans
• Cluster Analysis
• Confidence Intervals
• Computer Simulation
• Moyamoya Disease/diagnostic imaging
• Angiography, Digital Subtraction/statistics & numerical data
• Risk Assessment/methods
• Risk Assessment/statistics & numerical data
• Models, Statistical
• Data Interpretation, Statistical

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Grants

• KO 4680/4-1 Deutsche Forschungsgemeinschaft
• Deutsche Forschungsgemeinschaft

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Affiliation(s)

Erin Sprünken Institute of Biometry and Clinical EpidemiologyCharité ‐ Universitätsmedizin BerlinBerlinGermany
Robert Mertens Department of NeurosurgeryCharité ‐ Universitätsmedizin BerlinBerlinGermany
Frank Konietschke Institute of Biometry and Clinical EpidemiologyCharité ‐ Universitätsmedizin BerlinBerlinGermany

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An Epigenetic Locus Associated with Loss of Smell in COVID-19

BACKGROUND/AIM

Loss of smell, also known as anosmia, is a prevalent and often prolonged symptom following infection with SARS-CoV-2. While many patients regain olfactory function within weeks, a significant portion experience persistent anosmia lasting over a year post-infection. The underlying mechanisms responsible for this sensory deficit remain largely uncharacterized. Previous studies, including genome-wide association studies (GWAS), have identified genetic variants near the UGT2A1 and UGT2A2 genes that are linked to anosmia in COVID-19 patients. However, the role of epigenetic changes in the development and persistence of smell loss has not been well explored. In this study, we aimed to investigate epigenetic alterations in the form of DNA methylation in the UGT1A1 gene, which is a locus associated with olfactory dysfunction in COVID-19 patients.

METHODS

We analysed DNA methylation patterns in blood samples from two carefully matched cohorts of 20 COVID-19 patients each, which are differentiated by their olfactory function-those with normal smell (normosmia) and those suffering from smell loss (anosmia). The cohorts were matched for age and sex to minimize potential confounding factors.

RESULTS

Using quantitative analysis, we found significantly lower levels of DNA methylation in the UGT1A1 locus in the anosmia group compared to the normosmia group, with a 14% decrease in median methylation values in patients with smell loss (p < 0.0001). These findings highlight potential epigenomic alterations in the UGT1A1 gene that may contribute to the pathogenesis of anosmia following COVID-19 infection. Our results suggest that the methylation status at this locus could serve as a biomarker for olfactory dysfunction in affected individuals.

CONCLUSION

This study is among the first to describe epigenetic changes associated with smell loss in COVID-19, providing a foundation for future research into targeted interventions and potential therapeutic strategies aimed at reversing persistent anosmia. Further investigations involving larger cohorts and additional loci may help elucidate the complex interaction between genetic, epigenetic, and environmental factors influencing long-term sensory impairment post-COVID-19.

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

Epigenetic alterations in patients with anorexia nervosa-a systematic review

Anorexia nervosa (AN) is a complex metabolic and psychological disorder that is influenced by both heritable genetic components and environmental factors. Exposure to various environmental influences can lead to epigenetically induced changes in gene expression. Epigenetic research in AN is still in its infancy, and studies to date are limited in determining clear, valid links to disease onset and progression are limited. Therefore, the aim of this systematic review was to compile and critically evaluate the available results of epigenetic studies specifically in AN and to provide recommendations for future studies. In accordance with the PRISMA guidelines, a systematic literature search was performed in three different databases (PubMed, Embase, and Web of Science) through May 2023. Twenty-three original papers or conference abstracts on epigenetic studies in AN were collected. Epigenome-wide association studies (EWASs), which analyze DNA methylation across the genome in patients with AN and identify potential disease-relevant changes in promoter/regulatory regions of genes, are the most promising for future research. To date, five EWASs on AN have been published, suggesting a potential reversibility of malnutrition-induced epigenetic changes once patients recover. Hence, determining differential DNA methylation levels could serve as a biomarker for disease status or early diagnosis and might be involved in disease progression or chronification. For future research, EWASs with a larger sample size, longitudinal study design and uniform methods should be performed to contribute to the understanding of the pathophysiology of AN, the development of individual interventions and a better prognosis for affected patients.

Environmental Factor Index (EFI): A Novel Approach to Measure the Strength of Environmental Influence on DNA Methylation in Identical Twins

BACKGROUND/OBJECTIVES

The dynamic interaction between genomic DNA, epigenetic modifications, and phenotypic traits was examined in identical twins. Environmental perturbations can induce epigenetic changes in DNA methylation, influencing gene expression and phenotypes. Although DNA methylation mediates gene-environment correlations, the quantitative effects of external factors on DNA methylation remain underexplored. This study aimed to quantify these effects using a novel approach.

METHODS

A cohort study was conducted on healthy monozygotic twins to evaluate the influence of environmental stimuli on DNA methylation. We developed the Environmental Factor Index (EFI) to identify methylation sites showing statistically significant changes in response to environmental stimuli. We analyzed the identified sites for associations with disorders, DNA methylation markers, and CpG islands.

RESULTS

The EFI identified methylation sites that exhibited significant associations with genes linked to various disorders, particularly cancer. These sites were overrepresented on CpG islands compared to other genomic features, highlighting their regulatory importance.

CONCLUSIONS

The EFI is a valuable tool for understanding the molecular mechanisms underlying disease pathogenesis. It provides insights into the development of preventive and therapeutic strategies and offers a new perspective on the role of environmental factors in epigenetic regulation.

Different genome-wide DNA methylation patterns in CD4+ T lymphocytes and CD14+ monocytes characterize relapse and remission of multiple sclerosis: Focus on GNAS

BACKGROUND

Relapsing-remitting multiple sclerosis (RRMS) is a most common form of multiple sclerosis in which periods of neurological worsening are followed by periods of clinical remission. RRMS relapses are caused by an acute autoimmune inflammatory process, which can occur in any area of the central nervous system. Although development of exacerbation cannot yet be accurately predicted, various external factors are known to affect its risk. These factors may trigger the pathological process through epigenetic mechanisms of gene expression regulation, first of all, through changes in DNA methylation.

METHODS

In the present work, we for the first time analyzed genome-wide DNA methylation patterns in CD4+ T lymphocytes and CD14+ monocytes of the same RRMS patients in relapse and remission. The effects of the differential methylation on gene expression were studied using qPCR.

RESULTS

We found 743 differentially methylated CpG positions (DMPs) in CD4+ cells and only 113 DMPs in CD14+ cells. They were mostly hypermethylated in RRMS relapse in both cell populations. However, the proportion of hypermethylated DMPs (as well as DMPs located within or in close proximity to CpG islands) was significantly higher in CD4+ T lymphocytes. In CD4+ and CD14+ cells we identified 469 and 67 DMP-containing genes, respectively; 25 of them were common for two cell populations. When we conducted a search for differentially methylated genomic regions (DMRs), we found a CD4+ specific DMR hypermethylated in RRMS relapse (adj. p = 0.03) within the imprinted GNAS locus. Total level of the protein-coding GNAS transcripts in CD4+ T cells decreased significantly in the row from healthy control to RRMS remission and then to RRMS relapse (adj. p = 3.1 × 10-7 and 0.011, respectively).

CONCLUSION

Our findings suggest that the epigenetic mechanism of DNA methylation in immune cells contributes to the development of RRMS relapse. Further studies are now required to validate these results and shed light on the molecular mechanisms underlying the observed GNAS methylation and expression changes.

Epigenome-wide association study of fluoride exposure during early adolescence and DNA methylation among U.S. children

Exposure to fluoride in early childhood has been associated with altered cognition, intelligence, attention, and neurobehavior. Fluoride-related neurodevelopment effects have been shown to vary by sex and very little is known about the mechanistic processes involved. There is limited research on how fluoride exposure impacts the epigenome, potentially leading to changes in DNA methylation of specific genes regulating key developmental processes. In the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS), urine samples were analyzed using a microdiffusion method to determine childhood urinary fluoride adjusted for specific gravity (CUFsg) concentrations. Whole blood DNA methylation was assessed using the Infinium MethylationEPIC BeadChip 850 k Array. In a cross-sectional analysis, we interrogated epigenome-wide DNA methylation at 775,141 CpG loci across the methylome in relation to CUFsg concentrations in 272 early adolescents at age 12 years. Among all participants, higher concentrations of CUF were associated with differential methylation of one CpG (p < 6 × 10-8) located in the gene body of GBF1 (cg25435255). Among females, higher concentrations of CUFsg were associated with differential methylation of 7 CpGs; only three CpGs were differentially methylated among males with no overlap of significant CpGs observed among females. Secondary analyses revealed several differentially methylated regions (DMRs) and CpG loci mapping to genes with key roles in psychiatric outcomes, social interaction, and cognition, as well as immunologic and metabolic phenotypes. While fluoride exposure may impact the epigenome during early adolescence, the functional consequences of these changes are unclear warranting further investigation.

A methodology for gene level omics-WAS integration identifies genes influencing traits associated with cardiovascular risks: the Long Life Family Study

The Long Life Family Study (LLFS) enrolled 4953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that affect cardiovascular risks in the LLFS population, we developed a multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from rare-variant analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 64 significant genes after Bonferroni correction (p ≤ 2.8 × 10-7), 29 of which replicated in the Framingham Heart Study (FHS) cohort. Notably, 20 of the 29 replicated genes do not have a previously known trait-associated variant in the GWAS Catalog within 50 kb. Thirteen modules in Protein-Protein Interaction (PPI) networks are significantly enriched in genes with low meta-analysis p-values for at least one trait, three of which are replicated in the FHS cohort. The functional annotation of genes in these modules showed a significant over-representation of trait-related biological processes including sterol transport, protein-lipid complex remodeling, and immune response regulation. Among major findings, our results suggest a role of triglyceride-associated and mast-cell functional genes FCER1A, MS4A2, GATA2, HDC, and HRH4 in atherosclerosis risks. Our findings also suggest that lower expression of ATG2A, a gene we found to be associated with BMI, may be both a cause and consequence of obesity. Finally, our results suggest that ENPP3 may play an intermediary role in triglyceride-induced inflammation. Our pipeline is freely available and implemented in the Nextflow workflow language, making it easily runnable on any compute platform ( https://nf-co.re/omicsgenetraitassociation ).

Prenatal exposure to common infections and newborn DNA methylation: A prospective, population-based study

BACKGROUND

Infections during pregnancy have been robustly associated with adverse mental and physical health outcomes in offspring, yet the underlying molecular pathways remain largely unknown. Here, we examined whether exposure to common infections in utero associates with DNA methylation (DNAm) patterns at birth and whether this in turn relates to offspring health outcomes in the general population.

METHODS

Using data from 2,367 children from the Dutch population-based Generation R Study, we first performed an epigenome-wide association study to identify differentially methylated sites and regions at birth associated with prenatal infection exposure. We also examined the influence of infection timing by using self-reported cumulative infection scores for each trimester. Second, we sought to develop an aggregate methylation profile score (MPS) based on cord blood DNAm as an epigenetic proxy of prenatal infection exposure and tested whether this MPS prospectively associates with offspring health outcomes, including psychiatric symptoms, BMI, and asthma at ages 13-16 years. Third, we investigated whether prenatal infection exposure associates with offspring epigenetic age acceleration - a marker of biological aging. Across all analysis steps, we tested whether our findings replicate in 864 participants from an independent population-based cohort (ALSPAC, UK).

RESULTS

We observed no differentially methylated sites or regions in cord blood in relation to prenatal infection exposure, after multiple testing correction. 33 DNAm sites showed suggestive associations (p < 5e10 - 5; of which one was also nominally associated in ALSPAC), indicating potential links to genes associated with immune, neurodevelopmental, and cardiovascular pathways. While the MPS of prenatal infections associated with maternal reports of infections in the internal hold out sample in the Generation R Study (R2incremental = 0.049), it did not replicate in ALSPAC (R2incremental = 0.001), and it did not prospectively associate with offspring health outcomes in either cohort. Moreover, we observed no association between prenatal exposure to infections and epigenetic age acceleration across cohorts and clocks.

CONCLUSION

In contrast to prior studies, which reported DNAm differences in offspring exposed to severe infections in utero, we do not find evidence for associations between self-reported clinically evident common infections during pregnancy and DNAm or epigenetic aging in cord blood within the general pediatric population. Future studies are needed to establish whether associations exist but are too subtle to be statistically meaningful with present sample sizes, whether they replicate in a cohort with a more similar infection score as our discovery cohort, whether they occur in different tissues than cord blood, and whether other biological pathways may be more relevant for mediating the effect of prenatal common infection exposure on downstream offspring health outcomes.

Study protocol for Early Tracking of Childhood Health determinants (ETCHED): A longitudinal observational life course study

BACKGROUND

The prevalence of childhood obesity and diabetes continues to rise in the United States (US), especially among minority populations. The objective of the Early Tracking of Childhood Health Determinants (ETCHED) study is to investigate the role of adverse fetal and early-life risk exposures that contribute to the development of childhood obesity and metabolic risk.

METHODS

ETCHED is a longitudinal observational study of American Indian/Alaska Native (AI/AN) and Hispanic pregnant woman and their offspring. Pregnant mothers ≥ 18 years old are enrolled at a large public hospital system in the southwestern US. Enrolled mothers are followed through pregnancy, delivery, and the maternal/offspring dyad will be followed until the child's 18th birthday. At each maternal visit, questionnaires assessing medical history, diet, physical activity, sleep, perceived stress, and socioeconomic and sociocultural information are obtained. Standard laboratory tests during maternal visits include glycemic measures, lipids, and renal function. Additional bio samples obtained include venous blood samples and cord blood for obesity/metabolic biomarkers and genetic/epigenetic testing, urinalysis, placental tissue for examining functional pathways, breast milk for metabolomics, and stool for metabolites and microbiome analysis. The offspring will have 6 infant/toddler visits at 6-12 weeks, 4 months, 6 months, 18 months, 2 and 3 years respectively. Thereafter, they will undergo comprehensive research visits (major visits) at 4-5 years, 6-9 years, 10-13 years, and 14-17 years. The major visits in children include detailed medical history, anthropometry, developmental assessment, socioeconomic and environmental assessments (food insecurity, family structure, and childcare), feeding and activity, biochemical tests, genetics/epigenetic testing, and ultrasound elastography. Electronic health records will be reviewed for additional clinical information. The primary analysis will constitute estimation of correlation coefficients between continuous variables. The planned study duration in this ongoing study is 23-years.

DISCUSSION

This is a life course study that that will examine biological and environmental risk factors for obesity and cardiometabolic risk from the intrauterine period to early childhood and adolescence in a population with high-risk of obesity and type 2 diabetes in the United States. The ETCHED study would also provide a unique opportunity to combine multi-omics and clinical data to create novel integrative models to predict the cardiometabolic risk associated with childhood obesity and possibly identify etiopathogenetic mechanisms and future targets of intervention.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov identifier: NCT03481829. Updated July 19, 2024, https://clinicaltrials.gov/study/NCT03481829?cond=ETCHED&rank=1 .

Associations of healthy eating patterns with biological aging: national health and nutrition examination survey (NHANES) 1999-2018

BACKGROUND

Healthy dietary patterns have been negatively associated with methylation-based measures of biological age, yet previous investigations have been unable to establish the relationship between them and biological aging assessed through blood chemistry-based clinical biomarkers. We sought to assess the associations of 4 dietary metrics with 4 measures of biological age.

METHODS

Among 16,666 participants in NHANES 1999-2018, 4 dietary metrics [Dietary inflammatory index (DII), Dietary approaches to stop hypertension index (DASH), Alternate mediterranean diet score (aMED), and Healthy eating index-2015 (HEI-2015)] were calculated through the 'dietaryindex' R package. Twelve blood chemistry parameters were utilized to compute 4 indicators of biological age [homeostatic dysregulation (HD), allostatic load (AL), Klemera-Doubal method (KDM), and phenotypic age (PA)]. Binomial logistic regression models and restricted cubic spline (RCS) regression were employed to evaluate the associations.

RESULTS

All 4 dietary metrics were significantly associated with biological age acceleration or deceleration. In comparison to the lowest DII, the odds ratios (ORs) for accelerated HD, AL, KDM, and PA were 1.25 (1.08,1.45), 1.29 (1.11,1.50), 1.34 (1.08,1.65), and 1.61 (1.39,1.87) for the highest. The multivariable-adjusted ORs of the highest quartile of DASH, aMED, and HEI-2015 were 0.85 (0.73,0.97), 0.88 (0.74,1.04), and 0.84 (0.74,0.96) for HD, 0.64 (0.54,0.75), 0.61 (0.52,0.72), and 0.70 (0.59,0.82) for AL, 0.68 (0.54,0.85), 0.62 (0.50,0.76), and 0.71 (0.58,0.87) for KDM, and 0.50 (0.42,0.59), 0.64 (0.54,0.76), and 0.51 (0.44,0.58) for PA when compared with the lowest level. The findings were validated by the best-fitting dose-response curves for the associations. Among participants consuming dietary supplements (Pinteraction < 0.05), the positive effects of a healthy dietary pattern on biological aging were more pronounced. Systemic immune inflammation index (SII) and atherogenic index of plasma (AIP) were identified as being involved in and mediating the associations.

CONCLUSIONS

Biological aging assessed through blood chemistry-based clinical biomarkers is negatively associated with diet quality. The anti-aging benefits of improving the diet may be due to its ability to reduce inflammation and lower blood lipids.

AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS), a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI), a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features.

MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data

Epigenome-wide association studies (EWAS) are susceptible to widespread confounding caused by population structure and genetic relatedness. Nevertheless, kinship estimation is challenging in EWAS without genotyping data. Here, we proposed MethylGenotyper, a method that for the first time enables accurate genotyping at thousands of single nucleotide polymorphisms (SNPs) directly from commercial DNA methylation microarrays. We modeled the intensities of methylation probes near SNPs with a mixture of three beta distributions corresponding to different genotypes and estimated parameters with an expectation-maximization algorithm. We conducted extensive simulations to demonstrate the performance of the method. When applying MethylGenotyper to the Infinium EPIC array data of 4662 Chinese samples, we obtained genotypes at 4319 SNPs with a concordance rate of 98.26%, enabling the identification of 255 pairs of close relatedness. Furthermore, we showed that MethylGenotyper allows for the estimation of both population structure and cryptic relatedness among 702 Australians of diverse ancestry. We also implemented MethylGenotyper in a publicly available R package (https://github.com/Yi-Jiang/MethylGenotyper) to facilitate future large-scale EWAS.

Imprinting as Basis for Complex Evolutionary Novelties in Eutherians

The epigenetic phenomenon of genomic imprinting is puzzling. While epigenetic modifications in general are widely known in most species, genomic imprinting in the animal kingdom is restricted to autosomes of therian mammals, mainly eutherians, and to a lesser extent in marsupials. Imprinting causes monoallelic gene expression. It represents functional haploidy of certain alleles while bearing the evolutionary cost of diploidization, which is the need of a complex cellular architecture and the danger of producing aneuploid cells by mitotic and meiotic errors. The parent-of-origin gene expression has stressed many theories. Most prominent theories, such as the kinship (parental conflict) hypothesis for maternally versus paternally derived alleles, explain only partial aspects of imprinting. The implementation of single-cell transcriptome analyses and epigenetic research allowed detailed study of monoallelic expression in a spatial and temporal manner and demonstrated a broader but much more complex and differentiated picture of imprinting. In this review, we summarize all these aspects but argue that imprinting is a functional haploidy that not only allows a better gene dosage control of critical genes but also increased cellular diversity and plasticity. Furthermore, we propose that only the occurrence of allele-specific gene regulation mechanisms allows the appearance of evolutionary novelties such as the placenta and the evolutionary expansion of the eutherian brain.

Genome-wide DNA methylation profiling in blood reveals epigenetic signature of incident acute coronary syndrome

DNA methylation (DNAm) has been implicated in acute coronary syndrome (ACS), but the causality remains unclear in cross-sectional studies. Here, we conduct a prospective epigenome-wide association study of incident ACS in two Chinese cohorts (discovery: 751 nested case-control pairs; replication: 476 nested case-control pairs). We identified and validated 26 differentially methylated positions (DMPs, false discovery rate [FDR] <0.05), including three mapped to known cardiovascular disease genes (PRKCZ, PRDM16, EHBP1L1) and four with causal evidence from Mendelian randomization (PRKCZ, TRIM27, EMC2, EHBP1L1). Two hypomethylated DMPs were negatively correlated with the expression in blood of their mapped genes (PIGG and EHBP1L1), which were further found to overexpress in leukocytes and/or atheroma plaques. Finally, our DMPs could substantially improve the prediction of ACS over traditional risk factors and polygenic scores. These findings demonstrate the importance of DNAm in the pathogenesis of ACS and highlight DNAm as potential predictive biomarkers and treatment targets.

Whole Blood DNA Methylation Changes Are Associated with Anti-TNF Drug Concentration in Patients with Crohn's Disease

BACKGROUND AND AIMS

Anti-tumour necrosis factor [TNF] treatment failure in patients with inflammatory bowel disease [IBD] is common and frequently related to low drug concentrations. In order to identify patients who may benefit from dose optimisation at the outset of anti-TNF therapy, we sought to define epigenetic biomarkers in whole blood at baseline associated with anti-TNF drug concentrations at week 14.

METHODS

DNA methylation from 1104 whole blood samples from 385 patients in the Personalised Anti-TNF Therapy in Crohn's disease [PANTS] study were assessed using the Illumina EPIC Beadchip [v1.0] at baseline and weeks 14, 30, and 54. We compared DNA methylation profiles in anti-TNF-treated patients who experienced primary non-response at week 14 if they were assessed at subsequent time points and were not in remission at week 30 or 54 [infliximab n = 99, adalimumab n = 94], with patients who responded at week 14 and when assessed at subsequent time points were in remission at week 30 or 54 [infliximab n = 99, adalimumab n = 93].

RESULTS

Overall, between baseline and week 14, we observed 4999 differentially methylated positions [DMPs] annotated to 2376 genes following anti-TNF treatment. Pathway analysis identified 108 significant gene ontology terms enriched in biological processes related to immune system processes and responses. Epigenome-wide association [EWAS] analysis identified 323 DMPs annotated to 210 genes at baseline associated with higher anti-TNF drug concentrations at Week 14. Of these, 125 DMPs demonstrated shared associations with other common traits [proportion of shared CpGs compared with DMPs] including body mass index [23.2%], followed by C-reactive protein [CRP] [11.5%], smoking [7.4%], alcohol consumption per day [7.1%], and IBD type [6.8%]. EWAS of primary non-response to anti-TNF identified 20 DMPs that were associated with both anti-TNF drug concentration and primary non-response to anti-TNF with a strong correlation of the coefficients [Spearman's rho = -0.94, p <0.001].

CONCLUSION

Baseline DNA methylation profiles may be used as a predictor for anti-TNF drug concentration at week 14 to identify patients who may benefit from dose optimisation at the outset of anti-TNF therapy.

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.

Epigenetic disease markers in primary sclerosing cholangitis and primary biliary cholangitis-methylomics of cholestatic liver disease

BACKGROUND

The epigenome, the set of modifications to DNA and associated molecules that control gene expression, cellular identity, and function, plays a major role in mediating cellular responses to outside factors. Thus, evaluation of the epigenetic state can provide insights into cellular adaptions occurring over the course of disease.

METHODS

We performed epigenome-wide association studies of primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) using the Illumina MethylationEPIC Bead Chip.

RESULTS

We found evidence of increased epigenetic age acceleration and differences in predicted immune cell composition in patients with PSC and PBC. Epigenetic profiles demonstrated differences in predicted protein levels including increased levels of tumor necrosis factor receptor superfamily member 1B in patients with cirrhotic compared to noncirrhotic PSC and PBC. Epigenome-wide association studies of PSC discovered strongly associated 5'-C-phosphate-G-3' sites in genes including vacuole membrane protein 1 and SOCS3, and epigenome-wide association studies of PBC found strong 5'-C-phosphate-G-3' associations in genes including NOD-like receptor family CARD domain containing 5, human leukocyte antigen-E, and PSMB8. Analyses identified disease-associated canonical pathways and upstream regulators involved with immune signaling and activation of macrophages and T-cells. A comparison of PSC and PBC data found relatively little overlap at the 5'-C-phosphate-G-3' and gene levels with slightly more overlap at the level of pathways and upstream regulators.

CONCLUSIONS

This study provides insights into methylation profiles of patients that support current concepts of disease mechanisms and provide novel data to inspire future research. Studies to corroborate our findings and expand into other -omics layers will be invaluable to further our understanding of these rare diseases with the goal to improve and individualize prognosis and treatment.

Epigenetics of cerebrovascular diseases: an update review of clinical studies

Cerebrovascular diseases, especially stroke, are critical and heterogenous clinical conditions associated with high mortality and chronic disability. Genome-wide association studies reveal substantial stroke heritability, though specific genetic variants account for a minor fraction of stroke risk, suggesting an essential role for the epigenome. Epigenome-wide association studies and candidate gene approaches show that DNA methylation patterns significantly influence stroke susceptibility. Additionally, chromatin remodelers and non-coding RNA regulate gene expression in response to ischemic conditions. In this updated review, we summarized the progress of knowledge on epigenetics in the field of ischemic stroke underlying opportunities and challenges.

Gut microbiota and epigenetic choreography: Implications for human health: A review

The interwoven relationship between gut microbiota and the epigenetic landscape constitutes a pivotal axis in understanding human health and disease. Governed by a myriad of dietary, genetic, and environmental influences, the gut microbiota orchestrates a sophisticated metabolic interplay, shaping nutrient utilization, immune responses, and defenses against pathogens. Recent strides in genomics and metabolomics have shed light on the intricate connections between these microbial influencers and the host's physiological dynamics, presenting a dynamic panorama across diverse disease spectra. DNA methylation and histone modifications, as key players in epigenetics, intricately align with the dynamic orchestration of the gut microbiota. This seamless collaboration, notably evident in conditions like inflammatory bowel disease and obesity, has captured the attention of researchers, prompting an exploration of its nuanced choreography. Nevertheless, challenges abound. Analyzing data is intricate due to the multifaceted nature of the gut microbiota and the limitations of current analytical methods. This underscores the need for a multidisciplinary approach, where diverse disciplines converge to pave innovative research pathways. The integration of insights from microbiome and epigenome studies assumes paramount importance in unraveling the complexities of this intricate partnership. Deciphering the synchronized interactions within this collaboration offers a deeper understanding of these delicate interplays, potentially heralding revolutionary strides in treatment modalities and strategies for enhancing public health.

Genetic and Epigenetic Landscape for Drug Development in Polycystic Ovary Syndrome

The treatment of polycystic ovary syndrome (PCOS) faces challenges as all known treatments are merely symptomatic. The US Food and Drug Administration has not approved any drug specifically for treating PCOS. As the significance of genetics and epigenetics rises in drug development, their pivotal insights have greatly enhanced the efficacy and success of drug target discovery and validation, offering promise for guiding the advancement of PCOS treatments. In this context, we outline the genetic and epigenetic advancement in PCOS, which provide novel insights into the pathogenesis of this complex disease. We also delve into the prospective method for harnessing genetic and epigenetic strategies to identify potential drug targets and ensure target safety. Additionally, we shed light on the preliminary evidence and distinctive challenges associated with gene and epigenetic therapies in the context of PCOS.

Epigenetic link between Agent Orange exposure and type 2 diabetes in Korean veterans

Conflicting findings have been reported regarding the association between Agent Orange (AO) exposure and type 2 diabetes. This study aimed to examine whether AO exposure is associated with the development of type 2 diabetes and to verify the causal relationship between AO exposure and type 2 diabetes by combining DNA methylation with DNA genotype analyses. An epigenome-wide association study and DNA genotype analyses of the blood of AO-exposed and AO-unexposed individuals with type 2 diabetes and that of healthy controls were performed. Methylation quantitative trait locus and Mendelian randomisation analyses were performed to evaluate the causal effect of AO-exposure-identified CpGs on type 2 diabetes. AO-exposed individuals with type 2 diabetes were associated with six hypermethylated CpG sites (cg20075319, cg21757266, cg05203217, cg20102280, cg26081717, and cg21878650) and one hypo-methylated CpG site (cg07553761). Methylation quantitative trait locus analysis showed the methylation levels of some CpG sites (cg20075319, cg20102280, and cg26081717) to be significantly different. Mendelian randomisation analysis showed that CpG sites that were differentially methylated in AO-exposed individuals were causally associated with type 2 diabetes; the reverse causal effect was not significant. These findings reflect the need for further epigenetic studies on the causal relationship between AO exposure and type 2 diabetes.

Rockfish: A transformer-based model for accurate 5-methylcytosine prediction from nanopore sequencing

DNA methylation plays an important role in various biological processes, including cell differentiation, ageing, and cancer development. The most important methylation in mammals is 5-methylcytosine mostly occurring in the context of CpG dinucleotides. Sequencing methods such as whole-genome bisulfite sequencing successfully detect 5-methylcytosine DNA modifications. However, they suffer from the serious drawbacks of short read lengths and might introduce an amplification bias. Here we present Rockfish, a deep learning algorithm that significantly improves read-level 5-methylcytosine detection by using Nanopore sequencing. Rockfish is compared with other methods based on Nanopore sequencing on R9.4.1 and R10.4.1 datasets. There is an increase in the single-base accuracy and the F1 measure of up to 5 percentage points on R.9.4.1 datasets, and up to 0.82 percentage points on R10.4.1 datasets. Moreover, Rockfish shows a high correlation with whole-genome bisulfite sequencing, requires lower read depth, and achieves higher confidence in biologically important regions such as CpG-rich promoters while being computationally efficient. Its superior performance in human and mouse samples highlights its versatility for studying 5-methylcytosine methylation across varied organisms and diseases. Finally, its adaptable architecture ensures compatibility with new versions of pores and chemistry as well as modification types.

Advancing personalized medicine in neurodegenerative diseases: The role of epigenetics and pharmacoepigenomics in pharmacotherapy

About 80 % of brain disorders have a genetic basis. The pathogenesis of most neurodegenerative diseases is associated with a myriad of genetic defects, epigenetic alterations (DNA methylation, histone/chromatin remodeling, miRNA dysregulation), and environmental factors. The emergence of new sequencing technologies and tools to study the epigenome has led to identifying predictive biomarkers for earlier diagnosis, opening up the possibility of prophylactical interventions. As a result, advances in pharmacogenetics and pharmacoepigenomics now allow for personalized treatments based on the profile of each patient and the specific genetic and epigenetic mechanisms involved. This Review highlights the complexity of neurodegenerative diseases and the variability in patient responses to pharmacotherapy, emphasizing the influence of genetic polymorphisms on the pharmacokinetics and pharmacodynamics of drugs used to treat those conditions. We specifically discuss the potential modulatory effect of several genetic polymorphisms associated with an increased risk of developing different neurodegenerative diseases. We explore genetic and genomic technologies and the potential of analyzing individual-specific drug metabolism to predict and influence drug response and associated clinical outcomes. We also provide insights into the mechanism of action of the drugs under investigation and their potential impact on disease-modifying pathways. Finally, the Review underscores the great potential of this field to enhance the effectiveness and safety of drug treatments through personalized medicine.

Identification of a DNA-methylome-based signature for prognosis prediction in driver gene-negative lung adenocarcinoma

"Driver gene-negative" lung adenocarcinoma (LUAD) was of rare treatment options and a poor prognosis. Presently, for them, few biomarkers are available for stratification analysis to make appropriate treatment strategy. This study aimed to develop a DNA-methylome-based signature to realize the precise risk-stratifying. Here, an Illumina MethylationEPIC Beadchip was applied to obtain differentially methylated CpG sites (DMCs). A four-CpG-based signature, named as TLA, was successfully established, whose prognosis-predicting power was well verified in one internal (n = 78) and other external (n = 110) validation cohorts. Patients with high-risk scores had shorter overall survival (OS) in all cohorts [hazard ratio (HR): 11.79, 5.16 and 2.99, respectively]. Additionally, it can effectively divide patients into low-risk and high-risk groups, with significantly different OS in the diverse subgroups stratified by the standard clinical parameters. As an independent prognostic factor, TLA may assist in improving the nomogram's 5-year OS-predicting ability (AUC 0.756, 95% CI:0.695-0.816), superior to TNM alone (AUC 0.644, 95% CI: 0.590-0.698). Additionally, the relationship of TLA-related genes, TAC1, LHX9, and ALX1, with prognosis and tumour invasion made them serve as potential therapy targets for driver gene-negative LUAD.

Mass spectrometry-based metabolomics study of nicotine exposure in THP-1 monocytes

The tobacco alkaloid nicotine is known for its activation of neuronal nicotinic acetylcholine receptors. Nicotine is consumed in different ways such as through conventional smoking, e-cigarettes, snuff or nicotine pouches. The use of snuff has been associated with several adverse health effects, such as inflammatory reactions of the oral mucosa and oral cavity cancer. We performed a metabolomic analysis of nicotine-exposed THP-1 human monocytes. Cells were exposed to 5 mM of the alkaloid for up to 4 h, and cell extracts and medium subjected to untargeted liquid chromatography high-resolution mass spectrometry. Raw data processing revealed 17 nicotine biotransformation products. Among these, cotinine and nornicotine were identified as the two major cellular biotransformation products. The application of multi- and univariate statistical analyses resulted in the annotation, up to a certain level of identification, of 12 compounds in the cell extracts and 13 compounds in the medium that were altered by nicotine exposure. Of these, four were verified as methylthioadenosine, cytosine, uric acid, and L-glutamate. Methylthioadenosine levels were affected in both cells and the medium, while cytosine, uric acid, and L-glutamate levels were affected in the medium only. The effects of smoking on the pathways involving these metabolites have been previously demonstrated in humans. Most of the other discriminating compounds, which were merely tentatively or not fully identified, were amino acids or amino acid derivatives. In conclusion, our preliminary data suggest that some of the potentially adverse effects related to smoking may also be expected when nicotine is consumed via snuff or nicotine pouches.

Negative association between higher maternal pre-pregnancy body mass index and breastfeeding outcomes is not mediated by DNA methylation

The benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated with low breast feeding is maternal body mass index (BMI), which is used as a measure of obesity. The negative relationship between maternal obesity and breastfeeding is likely caused by a variety of social, psychological, and physiological factors. Maternal obesity may also have a direct biological association with breastfeeding through changes in maternal DNA methylation. Here, we investigate this potential biological association using data from a UK-based cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). We find that pre-pregnancy body mass index (BMI) is associated with lower initiation to breastfeed and shorter breastfeeding duration. We conduct epigenome-wide association studies (EWAS) of pre-pregnancy BMI and breastfeeding outcomes, and run candidate-gene analysis of methylation sites associated with BMI identified via previous meta-EWAS. We find that DNA methylation at cg11453712, annotated to PHTP1, is associated with pre-pregnancy BMI. From our results, neither this association nor those at candidate-gene sites are likely to mediate the link between pre-pregnancy BMI and breastfeeding.

Epigenetic insights to pediatric uropathology: Celebrating the fundamental biology vision of Tony Khoury

INTRODUCTION

Many pediatric urology conditions affect putatively normal tissues or appear too commonly to be based solely on specific DNA mutations. Understanding epigenetic mechanisms in pediatric urology, therefore, has many implications that can impact cell and tissue responses to settings, such as environmental and hormonal influences on urethral development, uropathogenic infections, obstructive stimuli, all of which originate externally or extracellularly. Indeed, the cell's response to external stimuli is often mediated epigenetically. In this commentary, we highlight work on the critical role that epigenetic machinery, such as DNA methyltransferases (DNMTs), Enhancer of Zeste Polycomb Repressive Complex 2 Subunit (EZH2), and others play in regulating gene expression and cellular functions in three urological contexts.

DESIGN

Animal and cellular constructs were used to model clinical pediatric uropathology. The hypertrophy, trabeculation, and fibrosis of the chronically obstructed bladder was explored using smooth muscle cell models employing disorganised vs. normal extracellular matrix (ECM), as well as a new animal model of chronic obstructive bladder disease (COBD) which retains its pathologic features even after bladder de-obstruction. Cell models from human and murine hypospadias or genital tubercles (GT) were used to illustrate developmental responses and epigenetic dependency of key developmental genes. Finally, using bladder urothelial and organoid culture systems, we examined activity of epigenetic machinery in response to non uropathogenic vs. uropathogenic E.coli (UPEC). DNMT and EZH2 expression and function were interrogated in these model systems.

RESULTS

Disordered ECM exerted a principal mitogenic and epigenetic role for on bladder smooth muscle both in vitro and in CODB in vivo. Key genes, e.g., BDNF and KCNB2 were under epigenetic regulation in actively evolving obstruction and COBD, though each condition showed distinct epigenetic responses. In models of hypospadias, estrogen strongly dysregulated WNT and Hox expression, which was normalized by epigenetic inhibition. Finally, DNA methylation machinery in the urothelium showed specific activation when challenged by uropathogenic E.coli. Similarly, UPEC induces hypermethylation and downregulation of the growth suppressor p16INK4A. Moreover, host cells exposed to UPEC produced secreted factors inducing epigenetic responses transmissible from one affected cell to another without ongoing bacterial presence.

DISCUSSION

Microenvironmental influences altered epigenetic activity in the three described urologic contexts. Considering that many obstructed bladders continue to display abnormal architecture and dysfunction despite relief of obstruction similar to after resection of posterior valves or BPH, the epigenetic mechanisms described highlight novel approaches for understanding the underlying smooth muscle myopathy of this crucial clinical problem. Similarly, there is evidence for an epigenetic basis of xenoestrogen on development of hypospadias, and UTI-induced pan-urothelial alteration of epigenetic marks and propensity for subsequent (recurrent) UTI. The impact of mechanical, hormonal, infectious triggers on genitourinary epigenetic machinery activity invite novel avenues for targeting epigenetic modifications associated with these non-cancer diseases in urology. This includes the use of deactivated CRISPR-based technologies for precise epigenome targeting and editing. Overall, we underscore the importance of understanding epigenetic regulation in pediatric urology for the development of innovative therapeutic and management strategies.

DNA methylation variations underlie lettuce domestication and divergence

BACKGROUND

Lettuce (Lactuca sativa L.) is an economically important vegetable crop worldwide. Lettuce is believed to be domesticated from a single wild ancestor Lactuca serriola and subsequently diverged into two major morphologically distinct vegetable types: leafy lettuce and stem lettuce. However, the role of epigenetic variation in lettuce domestication and divergence remains largely unknown.

RESULTS

To understand the genetic and epigenetic basis underlying lettuce domestication and divergence, we generate single-base resolution DNA methylomes from 52 Lactuca accessions, including major lettuce cultivars and wild relatives. We find a significant increase of DNA methylation during lettuce domestication and uncover abundant epigenetic variations associated with lettuce domestication and divergence. Interestingly, DNA methylation variations specifically associated with leafy and stem lettuce are related to regulation and metabolic processes, respectively, while those associated with both types are enriched in stress responses. Moreover, we reveal that domestication-induced DNA methylation changes could influence expression levels of nearby and distal genes possibly through affecting chromatin accessibility and chromatin loop.

CONCLUSION

Our study provides population epigenomic insights into crop domestication and divergence and valuable resources for further domestication for diversity and epigenetic breeding to boost crop improvement.

Epigenetic Aging and Musculoskeletal Outcomes in a Cohort of Women Living With HIV

BACKGROUND

The relationship between accelerated epigenetic aging and musculoskeletal outcomes in women with HIV (WWH) has not been studied.

METHODS

We measured DNA methylation age using the Infinium MethylationEPIC BeadChip in a cohort from the Women's Interagency HIV Study (n = 190) with measures of bone mineral density (BMD) and physical function. We estimated 6 biomarkers of epigenetic aging-epigenetic age acceleration (EAA), extrinsic EAA, intrinsic EAA, GrimAge, PhenoAge, and DNA methylation-estimated telomere length-and evaluated associations of epigenetic aging measures with BMD and physical function. We also performed epigenome-wide association studies to examine associations of DNA methylation signatures with BMD and physical function.

RESULTS

This study included 118 WWH (mean age, 49.7 years; 69% Black) and 72 without HIV (mean age, 48.9 years; 69% Black). WWH had higher EAA (mean ± SD, 1.44 ± 5.36 vs -1.88 ± 5.07; P < .001) and lower DNA methylation-estimated telomere length (7.13 ± 0.31 vs 7.34 ± 0.23, P < .001) than women without HIV. There were no significant associations between accelerated epigenetic aging and BMD. Rather, measures of accelerated epigenetic aging were associated with lower physical function.

CONCLUSIONS

Accelerated epigenetic aging was observed in WWH as compared with women without HIV and was associated with lower physical function in both groups.

Role of Histone Modifications in Kidney Fibrosis

Chronic kidney disease (CKD) is characterized by persistent kidney dysfunction, ultimately resulting in end-stage renal disease (ESRD). Renal fibrosis is a crucial pathological feature of CKD and ESRD. However, there is no effective treatment for this condition. Despite the complex molecular mechanisms involved in renal fibrosis, increasing evidence highlights the crucial role of histone modification in its regulation. The reversibility of histone modifications offers promising avenues for therapeutic strategies to block or reverse renal fibrosis. Therefore, a comprehensive understanding of the regulatory implications of histone modifications in fibrosis may provide novel insights into more effective and safer therapeutic approaches. This review highlights the regulatory mechanisms and recent advances in histone modifications in renal fibrosis, particularly histone methylation and histone acetylation. The aim is to explore the potential of histone modifications as targets for treating renal fibrosis.

Mitochondrial DNA: Inherent Complexities Relevant to Genetic Analyses

Mitochondrial DNA (mtDNA) exhibits distinct characteristics distinguishing it from the nuclear genome, necessitating specific analytical methods in genetic studies. This comprehensive review explores the complex role of mtDNA in a variety of genetic studies, including genome-wide, epigenome-wide, and phenome-wide association studies, with a focus on its implications for human traits and diseases. Here, we discuss the structure and gene-encoding properties of mtDNA, along with the influence of environmental factors and epigenetic modifications on its function and variability. Particularly significant are the challenges posed by mtDNA's high mutation rate, heteroplasmy, and copy number variations, and their impact on disease susceptibility and population genetic analyses. The review also highlights recent advances in methodological approaches that enhance our understanding of mtDNA associations, advocating for refined genetic research techniques that accommodate its complexities. By providing a comprehensive overview of the intricacies of mtDNA, this paper underscores the need for an integrated approach to genetic studies that considers the unique properties of mitochondrial genetics. Our findings aim to inform future research and encourage the development of innovative methodologies to better interpret the broad implications of mtDNA in human health and disease.

Mixed-Methods Study of Disability Self-Management in Mexican Americans With Osteoarthritis

BACKGROUND

Health disparities in osteoarthritis (OA) outcomes exist both in the occurrence and treatment of functional limitation and disability for Mexican Americans. Although the effect of self-management of chronic illness is well established, studies demonstrate little attention to self-management of function or disability, despite the strong potential effect on both and, consequently, on patients' lives.

OBJECTIVE

The purpose of this study pilot was to develop and test key variable relationships for a measure of disability self-management among Mexican Americans.

METHODS

In this sequential, two-phased, mixed-methods, biobehavioral pilot study of Mexican American women and men with OA, a culturally tailored measure of disability self-management was created, and initial relationships among key variables were explored.

RESULTS

First, a qualitative study of 19 adults of Mexican American descent born in Texas (United States) or Mexico was conducted. The Mexican American Disability Self-Management Scale was created using a descriptive content analysis of interview data. The scale was tested and refined, resulting in 18 items and a descriptive frequency of therapeutic management efforts. Second, correlations between study variables were estimated: Disability and function were negatively correlated. Disability correlated positively with social support and activity effort. Disability correlated negatively with disability self-management, pain, and C-reactive protein. Function was positively correlated with age, pain, and depression. Liver enzymes (alanine transaminase) correlated positively with pain and anxiety.

DISCUSSION

This mixed-methods study indicates directions for further testing and interventions for disability outcomes among Mexican Americans.

DNA methylation patterns of FKBP5 regulatory regions in brain and blood of humanized mice and humans

Humanized mouse models can be used to explore human gene regulatory elements (REs), which frequently lie in non-coding and less conserved genomic regions. Epigenetic modifications of gene REs, also in the context of gene x environment interactions, have not yet been explored in humanized mouse models. We applied high-accuracy measurement of DNA methylation (DNAm) via targeted bisulfite sequencing (HAM-TBS) to investigate DNAm in three tissues/brain regions (blood, prefrontal cortex and hippocampus) of mice carrying the human FK506-binding protein 5 (FKBP5) gene, an important candidate gene associated with stress-related psychiatric disorders. We explored DNAm in three functional intronic glucocorticoid-responsive elements (at introns 2, 5, and 7) of FKBP5 at baseline, in cases of differing genotype (rs1360780 single nucleotide polymorphism), and following application of the synthetic glucocorticoid dexamethasone. We compared DNAm patterns in the humanized mouse (N = 58) to those in human peripheral blood (N = 447 and N = 89) and human postmortem brain prefrontal cortex (N = 86). Overall, DNAm patterns in the humanized mouse model seem to recapitulate DNAm patterns observed in human tissue. At baseline, this was to a higher extent in brain tissue. The animal model also recapitulated effects of dexamethasone on DNAm, especially in peripheral blood and to a lesser extent effects of genotype on DNAm. The humanized mouse model could thus assist in reverse translation of human findings in psychiatry that involve genetic and epigenetic regulation in non-coding elements.

The pharmacoepigenetic paradigm in cancer treatment

Epigenetic modifications, characterized by changes in gene expression without altering the DNA sequence, play a crucial role in the development and progression of cancer by significantly influencing gene activity and cellular function. This insight has led to the development of a novel class of therapeutic agents, known as epigenetic drugs. These drugs, including histone deacetylase inhibitors, histone acetyltransferase inhibitors, histone methyltransferase inhibitors, and DNA methyltransferase inhibitors, aim to modulate gene expression to curb cancer growth by uniquely altering the epigenetic landscape of cancer cells. Ongoing research and clinical trials are rigorously evaluating the efficacy of these drugs, particularly their ability to improve therapeutic outcomes when used in combination with other treatments. Such combination therapies may more effectively target cancer and potentially overcome the challenge of drug resistance, a significant hurdle in cancer therapy. Additionally, the importance of nutrition, inflammation control, and circadian rhythm regulation in modulating drug responses has been increasingly recognized, highlighting their role as critical modifiers of the epigenetic landscape and thereby influencing the effectiveness of pharmacological interventions and patient outcomes. Epigenetic drugs represent a paradigm shift in cancer treatment, offering targeted therapies that promise a more precise approach to treating a wide spectrum of tumors, potentially with fewer side effects compared to traditional chemotherapy. This progress marks a step towards more personalized and precise interventions, leveraging the unique epigenetic profiles of individual tumors to optimize treatment strategies.

Hydration water drives the self-assembly of guanosine monophosphate

Guanosine monophosphate (GMP) is a nucleotide that can self-assemble in aqueous solution under certain conditions. An understanding of the process at the molecular level is an essential step to comprehend the involvement of DNA substructures in transcription and replication, as well as their relationship to genetic diseases such as cancer. We present the temperature-dependent terahertz (1.5-12 THz, 50-400 cm-1) absorptivity spectra of aqueous Na2 GMP solution in comparison with the aqueous solutions of other RNA nucleotides. Distinct absorption features were observed in the spectrum of GMP, which we attribute to the intramolecular modes of the self-assemblies (i.e., G-complexes) that, at 1 M, start to form at 313 K and below. Changes in broad-band features of the terahertz spectrum were also observed, which we associate with the release of hydration water in the temperature-dependent formation of guanine quadruplexes. Using a state-of-the-art THz calorimetry approach correlating spectroscopic to thermodynamic changes, we propose a molecular mechanism of hydrophilic hydration driving GMP self-assembly as a function of temperature. The free energy contribution of hydrophilic hydration is shown as a decisive factor in guanine-quadruplex formation. Our findings spotlight the role of hydration in the formation of macromolecular structures and suggest the potential of hydration tuning for regulating DNA transcription and replication.

Molecular pathological approach to cancer epigenomics and its clinical application

Careful microscopic observation of histopathological specimens, accumulation of large numbers of high-quality tissue specimens, and analysis of molecular pathology in relation to morphological features are considered to yield realistic data on the nature of multistage carcinogenesis. Since the morphological hallmark of cancer is disruption of the normal histological structure maintained through cell-cell adhesiveness and cellular polarity, attempts have been made to investigate abnormalities of the cadherin-catenin cell adhesion system in human cancer cells. It has been shown that the CDH1 tumor suppressor gene encoding E-cadherin is silenced by DNA methylation, suggesting that a "double hit" involving DNA methylation and loss of heterozygosity leads to carcinogenesis. Therefore, in the 1990s, we focused on epigenomic mechanisms, which until then had not received much attention. In chronic hepatitis and liver cirrhosis associated with hepatitis virus infection, DNA methylation abnormalities were found to occur frequently, being one of the earliest indications that such abnormalities are present even in precancerous tissue. Aberrant expression and splicing of DNA methyltransferases, such as DNMT1 and DNMT3B, was found to underlie the mechanism of DNA methylation alterations in various organs. The CpG island methylator phenotype in renal cell carcinoma was identified for the first time, and its therapeutic targets were identified by multilayer omics analysis. Furthermore, the DNA methylation profile of nonalcoholic steatohepatitis (NASH)-related hepatocellular carcinoma was clarified in groundbreaking studies. Since then, we have developed diagnostic markers for carcinogenesis risk in NASH patients and noninvasive diagnostic markers for upper urinary tract cancer, as well as developing a new high-performance liquid chromatography-based diagnostic system for DNA methylation diagnosis. Research on the cancer epigenome has revealed that DNA methylation alterations occur from the precancerous stage as a result of exposure to carcinogenic factors such as inflammation, smoking, and viral infections, and continuously contribute to multistage carcinogenesis through aberrant expression of cancer-related genes and genomic instability. DNA methylation alterations at the precancerous stages are inherited by or strengthened in cancers themselves and determine the clinicopathological aggressiveness of cancers as well as patient outcome. DNA methylation alterations have applications as biomarkers, and are expected to contribute to diagnosis, as well as preventive and preemptive medicine.

Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins

To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.

"Air That Once Was Breath" Part 1: Wildfire-Smoke-Induced Mechanisms of Airway Inflammation - "Climate Change, Allergy and Immunology" Special IAAI Article Collection: Collegium Internationale Allergologicum Update 2023

BACKGROUND

Wildfires are a global concern due to their wide-ranging environmental, economic, and public health impacts. Climate change contributes to an increase in the frequency and intensity of wildfires making smoke exposure a more significant and recurring health concern for individuals with airway diseases. Some of the most prominent effects of wildfire smoke exposure are asthma exacerbations and allergic airway sensitization. Likely due to the delayed recognition of its health impacts in comparison with cigarette smoke and industrial or traffic-related air pollution, research on the composition, the mechanisms of toxicity, and the cellular/molecular pathways involved is poor or non-existent.

SUMMARY

This review discusses potential underlying pathological mechanisms of wildfire-smoke-related allergic airway disease and asthma. We focused on major gaps in understanding the role of wildfire smoke composition in the development of airway disease and the known and potential mechanisms involving cellular and molecular players of oxidative injury at the epithelial barrier in airway inflammation. We examine how PM2.5, VOCs, O3, endotoxin, microbes, and toxic gases may affect oxidative stress and inflammation in the respiratory mucosal barrier. We discuss the role of AhR in mediating smoke's effects in alarmin release and IL-17A production and how glucocorticoid responsiveness may be impaired by IL-17A-induced signaling and epigenetic changes leading to steroid-resistant severe airway inflammation.

KEY MESSAGE

Effective mitigation of wildfire-smoke-related respiratory health effects would require comprehensive research efforts aimed at a better understanding of the immune regulatory effects of wildfire smoke in respiratory health and disease.