Clinical Epigenetics

DNA methylation is an established biomarker of human ageing, and analysing CpGs grouped by transcript as functional units may reveal new insights into the processes of ageing. In this study, we analyzed the GSE87571 dataset (714 samples from 14-94 years) to assess the relationship between transcript-level methylation profiles and chronological age in human blood. This approach led to the creation of Epitage, a curated set of 48 transcripts from 13 genes identified through machine learning as having methylation profiles that strongly correlate with age (R2 [≥] 0.8). This analysis highlighted transcripts from the genes KCNS1, SPTBN4, and VTRNA1-2, which have been only rarely mentioned as age-related methylation markers in humans, suggesting them as underexplored candidates for future investigation. In addition, the list includes genes already implicated in aging or related pathways, such as ELOVL2, FHL2, KLF14, TRIM59, MIR29B2CHG, CALB1, OBSCN, PRRT1, OTUD7A, and SYNGR3. To validate models efficiently while ensuring reproducibility, we developed ugPlot, an open-source R package with a graphical user interface (GUI) that automates routine steps for training and testing hundreds of machine-learning models. The tool also streamlines dataset import and manipulation, reducing human error and generating publication-ready plots. Epitage thus provides a focused and accessible starting point for experimental and translational studies into the roles of DNA methylation and transcript regulation in human ageing.

BackgroundAgeing is a sex-specific process characterised by a progressive decline in physiological integrity. DNA methylation represents a primary epigenetic hallmark of ageing, yet sex-specific patterns of epigenetic ageing within and across tissues remain poorly understood. This study aims to address these gaps through an integrated analysis of sex-moderated epigenetic ageing across eight human tissues. MethodsA total of 137 DNA methylation datasets comprising over 36,000 individuals aged 10-114 years were analysed using a meta-analytic workflow to identify age-associated differentially methylated positions (aDMPs) and regions (aDMRs), meta-regression to assess sex moderation, and pathway enrichment analyses to interpret functional relevance. FindingsIndividual tissues displayed distinct age-related methylation trajectories, but some DMP sites showed consistent hyper- or hypomethylation across tissues. Across tissues, we identified 68,630 aDMPs (10%) robustly associated with ageing. Age-associated changes at the regional level were less common, with only 80 robust age-associated aDMRs detected across tissues, representing 0.09% of analysed regions. Sex moderation was observed for only 16 aDMPs (0.002%), indicating that sex effects on age-associated DNA methylation are largely tissue-specific rather than shared across tissues. InterpretationOur findings indicate that age-associated DNA methylation changes predominantly occur at isolated CpG sites rather than extended genomic regions and are strongly dependent on tissue and genomic context. The minimal overlap of sex-moderated methylation signals across tissues suggests that age-related sex differences at the epigenetic level are more likely attributable to tissue- and cell-type-specific variation rather than to broadly conserved epigenetic mechanisms shared across tissues. FundingThis study was funded by an Australian Research Council (ARC) Discovery project (DP200101830). Severine Lamon was funded by an ARC Future Fellowship (FT210100278). Nir Eynon was funded by NHMRC Investigator Grant (APP1194159), and a Hevolution/AFAR New Investigator Award in Aging Biology and Geroscience Research. Mandhri D. Abeysooryia was supported by an Australian Government Research Training Program (RTP) Scholarship. Research in context Evidence before this studyDNA methylation is widely recognised as a central epigenetic hallmark of ageing. Previous research has demonstrated that some age-related methylation changes are conserved across tissues, forming the basis of pan-tissue epigenetic clocks. Most studies to date have primarily examined age effects in isolation. Although biological sex influences ageing trajectories and susceptibility to nearly all age-related diseases, sex-moderated epigenetic ageing has received limited investigation. Specifically, pan-tissue clocks, including GrimAge and PhenoAge, are "sex-aware" but were trained and validated in mixed-sex cohorts, limiting their capacity to disentangle tissue-specific sex effects. Consequently, it remains unclear whether sex-moderated epigenetic ageing signals are shared across tissues or are tissue-specific. Added value of this studyThis study provides a large-scale, comprehensive multi-tissue analysis of sex-moderated epigenetic ageing, integrating 137 DNA methylation datasets across eight human tissues and more than 36,000 male and female individuals spanning the lifespan. Our findings show that while age-associated methylation changes are widespread at the CpG level, sex-moderated effects are rare and largely tissue-specific, with minimal overlap across tissues. Implications of all the available evidenceTogether, the available evidence indicates that epigenetic ageing is predominantly driven by shared, conserved age-related methylation changes, whereas sex differences in epigenetic ageing are modest and context dependent. These sex-related effects are more likely to reflect tissue- and cell-type-specific variation rather than widespread, shared mechanisms. This underscores the need to develop sex-specific epigenetic clocks and to conduct longitudinal cohort and intervention studies to more precisely characterise sex-specific dynamics of epigenetic ageing across tissues.

BackgroundAberrant DNA methylation is a hallmark of colorectal cancer (CRC). Yet, how DNA methylation is linked to transcriptional states, immune programs, and tissue resident microbiome within the same tumors has not been systematically analyzed. MethodsWe profiled genome-wide DNA methylation (Illumina MethylationEPIC) in 182 colon tumors and 76 adjacent normals from AC-ICAM, and integrated with matched transcriptomes, whole exome, microbiome, and clinical data. Tumor-specific methylation, promoter methylation-expression links, microbiome associations, and survival were analyzed and validated in TCGA-COAD. ResultsTumor and normal tissues exhibited distinct DNA methylation patterns, reflecting widespread epigenetic alterations in cancer. Pathway analysis identified two major tumor pathways regulated by DNA methylation. The first involved extracellular signaling and adhesion genes, with higher methylation linked to increased proliferation and lower immune infiltration. Similarly, higher tumor methylation in nitric oxide signaling was associated with reduced adaptive immune activity and interestingly, influenced immune-related survival. These findings were also validated in the TCGA-COAD cohort. An inverse methylation-expression pattern implicated modifications of TCR signaling in naive CD8, and interferon-/{beta} signaling which were hypermethylated and hypomethylated in tumors compared to normal, respectively. Combining methylation and microbiome revealed connections between Akkermansia muciniphila and TGF-{beta} and Prevotella nigrescens with MAPK signaling pathways. Finally, a methylation-based model using 43 promoters CpGs successfully identified patients with different survival outcomes, underscoring the clinical relevance of these epigenetic alterations in colon cancer. ConclusionDNA methylation shapes the molecular and immune landscape of colon cancer, altering signaling pathways and immune programs, interacting with the microbiome, and impacting patients survival.

BackgroundColorectal cancer (CRC) is a molecularly heterogeneous disease shaped by both genetic and epigenetic alterations. Approximately 15% of CRCs display widespread CpG island hypermethylation, known as the CpG Island Methylator Phenotype (CIMP). CIMP-high (CIMP-H) tumours frequently exhibit MLH1 promoter hypermethylation, leading to mismatch repair deficiency (MMRd) and microsatellite instability (MSI). However, DNA methylation patterns associated with MSI, independent of CIMP and MLH1 silencing, and the influence of clinical variables such as anatomical location and patient age on the CRC methylome remain poorly characterised. MethodsWe performed epigenome-wide DNA methylation profiling of 259 primary CRC tissue samples using the Illumina EPICv2 array, comparing differential methylation between MSI and microsatellite stable (MSS) CRC, adjusting for tumour purity, MLH1 promoter methylation, CIMP status, and anatomical location, to account for known confounders. We further evaluated the independent effects of anatomical location and patient age on global methylation patterns. ResultsEpigenome-wide differential methylation between MSS and MSI CRC was dominated by MLH1 promoter hypermethylation. After adjusting for MLH1 hypermethylation and CIMP status, we identified a distinct set of 656 CpG sites associated with MMRd independent of MLH1 silencing. These included hypermethylation at LRP6, GSK3{beta}, and CDK12, implicating altered WNT signalling and transcriptional regulation pathways. Comparison of MSI subgroups revealed the co-occurrence of MLH1 hypermethylation with promoter hypermethylation at TXNRD1. Anatomical location showed a strong independent effect on methylation patterns, while we observed only modest effects of patient age on the CRC methylome after adjustment for confounders. ConclusionsWe identified a distinct methylation profile distinguishing MSS and MSI CRC, including MLH1-independent markers of MMRd, as well as novel differentially methylated loci within MSI subgroups. We further showed that anatomical location has a strong independent impact on the CRC methylome. Together, these findings refine the molecular characterisation of CRC and highlight potential epigenetic markers that could inform patient stratification and precision oncology.

BackgroundWith the US population living longer, the risk, incidence, prevalence and severity for chronic kidney diseases become more abundant. Glomerular diseases are the leading cause for chronic and end-stage kidney disease. Yet, the cellular responses and the underlying mechanisms of progressive glomerular disease, which ultimately leads to glomerulosclerosis and loss of kidney function with advancing age, are poorly understood. MethodsKidneys of young (4 months-old), middle-aged (20 months-old) and aged (24 months-old) mice were separated into outer cortex and juxta-medullary region and processed for single nuclei transcriptomics. Focusing on the aging glomerulus data were analyzed using a state-of-the-art analysis pipeline dissecting out the cellular age- and kidney region-specific responses. ResultsGlobal analysis of the transcriptome reveals regional-specific differences that are detectable across multiple cell types exemplified by the expression of Napsa as a bona-fide juxta-medullary marker. In contrast aging led to rather cell type-specific responses. In the glomerulus, healthy podocytes were characterized by expression of canonical podocyte genes; conversely the senescent, aged podocytes were characterized by the down-regulation of canonical podocyte genes and the emergence of inflammatory and senescent signatures. Interestingly, these senescent podocytes were primarily located in the juxtamedullary region suggesting that juxtamedullary podocytes are more sensitive. Yet, instead of aging being defined by distinct cell states, the profiles, as well as ligand-receptor and pseudotime analyses suggest that podocytes aging is selective and coordinated, not universal degeneration. This was different to the other glomerular cell types, parietal epithelial cells, glomerular endothelial cells and mesangial cells. While they also as existed in different subpopulations, they exhibited little regional-, or age-depended changes. Finally proximal tubular aging manifested itself as discrete cellular states. ConclusionsThe single nuclei transcriptomics of the aging kidney provides a mechanistic explanation for regional susceptibility of nephrons and suggests that the future therapeutic strategies need to consider the cellular and spatial complexity of the glomerulus.

Many overgrowth syndromes are associated with increased risk of tumorigenesis and malignancies. Our group recently identified a frameshift variant in histone reader SPIN4 located on the X chromosome to be a new genetic cause for human overgrowth. In the current study, we investigated the prevalence of malignancies, along with body weight, body length, body composition and bone mineral density, in Spin4 knockout mice at 18 months of age. We found that male mice lacking Spin4 have increased number of tumors and increased body length, while body weight, body composition and bone mineral density were comparable with wild-type mice. We also analyzed publicly available expression data in various types of human cancers and looked for increased or decreased expression of genes that are implicated in overgrowth syndromes and act through epigenetic mechanisms. We found that the expression of SPIN4, EZH2, and DNMT3A to be elevated in many human cancers compared to the corresponding non-malignant tissue samples. Taken together, our current findings confirm that loss of SPIN4 causes overgrowth in mice (in terms of body length) and is associated with increased prevalence in neoplasia; but does not appear to affect adiposity or bone density.

BackgroundEpigenetic clocks based on DNA methylation (DNAm) are widely used indicators of biological aging; however, most established models have been developed using EPIC arrays and non-Japanese populations. The Methylation Screening Array (MSA), a cost-efficient platform with reduced CpG content, has not been evaluated for its capacity to support biological age estimation and biomarker prediction in Japanese cohorts. MethodsDNAm profiles and clinical laboratory measurements were obtained from 166 Japanese participants for model development; an independent cohort of 48 individuals processed at a separate institute was used for validation. A linear regression model was trained using the Elastic Net method to predict phenotypic age from MSA-derived methylation data, and a two-stage modeling (residual learning) framework integrating EPIC-based clock predictions with MSA-specific residual predictions was evaluated. Additional models were constructed to examine the predictability of 59 clinical biomarkers and their log-transformed variants, including sex-stratified analyses. ResultsThe MSA-based model accurately predicted phenotypic age in the validation dataset; prediction performance improved when the EPIC-based estimates were incorporated through the residual learning framework. Several clinical biomarkers, particularly those related to leukocyte composition and sex hormone regulation, were also predicted from the MSA data, although some markers were strongly affected by sex. Some of the nine constituent phenotypic age biomarkers were not individually predicted. ConclusionsMSA methylation profiles contain sufficient biological information for reliable prediction of epigenetic aging markers in Japanese individuals. These findings demonstrate the feasibility of applying cost-efficient MSA-based DNAm profiling for biological age prediction and provide a methodological foundation for expanding epigenetic biomarker applications in Japan.

BackgroundSmall-cell lung cancer (SCLC) represents 15% of lung cancers and with a 5-year survival rate under 7% remains one of the deadliest malignancies. Although initially responsive to chemotherapy, rapid recurrence and resistance are common. Epigenetic modifications, particularly DNA methylation, contribute to tumor progression and therapy resistance. Guadecitabine, a hypomethylating agent (HMA), has shown promising clinical activity when combined with carboplatin in preclinical models. We evaluated the combination of guadecitabine with carboplatin as a second-line treatment for extensive-stage SCLC (NCT03913455). Here we report methylome changes in peripheral blood mononuclear cell (PBMCs) collected at baseline and during treatment from patients on the trial. ResultsPMBC DNA was analyzed using Infinium HumanMethylationEPIC v1.0 bead chips. Data were processed and differentially methylated positions (DMPs) were identified and analyzed for pathway enrichment using bioinformatic approaches and immune deconvolution analyses were conducted to investigate the impact on immune cell composition. Direct comparison of PBMCs between cycle 2 day 5 (C2D5; post-treatment) vs cycle 1 day 1 (C1D1; pre-treatment) revealed a greater number of hypomethylated DMPs (380 DMPs in C2D5 vs C1D1 PBMCs; p < 0.05, |{beta}| > 20%). Moreover, when first compared with normal PBMCs from cancer-free controls, the number of hypomethylated DMPs was even greater in C2D5 than in C1D1 (1,771 vs 237 DMPs, respectively; p < 0.05, |{beta}| > 20%). Long interspersed nucleotide elements-1 (LINE-1) were also significantly hypomethylated in PBMCs after HMA treatment (C2D5), compared to C1D1. Pathway analysis of hypomethylated DMPs revealed significant alterations in key signaling pathways including NF-{kappa}B, Rho GTPase, pulmonary fibrosis, and p75 NTR in C1D1 vs C2D5. When normal PBMCs were compared to C1D1 PBMCs, changes in IL-3 signaling, Fc{gamma} receptor-mediated phagocytosis, and molecular mechanisms of cancer were observed. Deconvolution analysis revealed a significantly higher percentage of monocytes in C1D1 PBMCs vs normal PBMCs. However, after HMA treatment, percentages of monocytes and B cells decreased, while eosinophil percentage increased in C1D1 compared to C2D5 PBMCs. ConclusionIn the first study on the global impact of HMA treatment on PBMC methylomes in SCLC patients, DNA methylation changes associated with biological pathways related to PBMC function reveal shifts in distinct immune cell populations. SummaryMethylome changes in peripheral blood mononuclear cell (PBMCs) from small cell lung cancer (SCLC) patients treated with an epigenetic therapy revealed global hypomethylation and altered cancer signaling processes associated with tumor progression, immune response, therapy resistance and significant change in the proportion of immune cells. Integrating blood-based methylation biomarkers into clinical trials of epigenetic therapy and methylomic analysis of PBMCs provides direct monitoring of treatment effects in cancer patients, which may improve patient selection and enable real-time response assessment in patients receiving hypomethylating agents.

BackgroundLow mitochondrial DNA (mtDNA) abundance in blood cells has been associated with various diseases and major causes of mortality. However, the causal link and molecular mechanisms involved remain unclear, and previous studies have had limited follow-up durations. To address these gaps, we examined the relationship of blood mtDNA abundance with all-cause and cause-specific mortality over three decades, and integrated blood transcriptomic profiling to explore underlying molecular mechanisms. Our goal was to improve the understanding of blood mtDNA abundance as a potential early biomarker for major clinical conditions. Methods and findingsWe utilized the clinical and epidemiological data from the prospective OPERA cohort (Oulu Project Elucidating Risk of Atherosclerosis), comprising 1045 individuals initially assessed in the 1990s and followed for over three decades, with a second visit in the 2010s. Blood mtDNA was quantified using real-time quantitative polymerase chain reaction at both time points, and RNA-sequencing was performed on 450 follow-up blood samples. Lower blood mtDNA levels in the 1990s samples were significantly associated with increased overall morbidity and all-cause mortality, assessed up to the end of 2022. Similar trends were observed in a subset of 597 participants from the 2010s. When causes of death were categorized as "cardiovascular", "cancer", or "other", lower blood mtDNA levels predicted higher mortality across all categories. Transcriptomic analysis of the follow-up samples suggested that blood mtDNA variation may be linked to subclinical inflammation involving innate immunity. ConclusionsBlood cell mtDNA abundance shows promise as an early biomarker for general morbidity and mortality in the middle-aged population, although it is not specific to distinct causes of death. The underlying pathomechanism of lower blood mtDNA levels may involve inflammatory processes. These findings, combined with the three-decade follow-up, support the potential use of blood mtDNA in the primary prevention of morbidity and mortality of various etiology.

DNA methylation-based epigenetic clocks have been highlighted as promising biomarkers of ageing, and they have been shown to robustly predict morbidity and mortality. However, current literature is lacking a formal analysis of the increased prediction accuracy, or the added value, of the epigenetic clocks over traditional risk factors of common chronic diseases. Here, we have compared the most commonly used epigenetic clocks and traditional risk factors as predictors of incidence of ageing-associated non-communicable chronic disease in a 7-to-9-year follow-up in a middle-aged population cohort (n=1108, aged 34 to 49 years at baseline). In our cohort, a statistical model consisting of a combination of traditional risk factors outperforms any model including an epigenetic clock. The added value of epigenetic clock measurements over simple and affordable traditional risk factors should be clearly established, if epigenetic clocks are to be used in clinical settings or as tools of personal health monitoring.

Skeletal muscle atrophy and deconditioning contribute to functional limitation and disability in COPD. While transcriptome and DNA methylation changes accompany exercise in healthy muscle, their interaction with COPD status and ageing, and integrative analyses of methylome-transcriptome responses have not been explored. We performed gene expression and DNA methylation profiling in skeletal muscle of sedentary volunteers with COPD, age-matched older adults, and younger healthy individuals, before and during (1,4 and 8 weeks) supervised aerobic exercise training and after four weeks of detraining. Exercise induced transcriptomic and DNA methylation changes, but these responses were unaffected by COPD status or age. Subsequent analysis focusing on temporal exercise effects independent of disease or age revealed differential transcriptomic changes across time points, a subset of which significantly associated with DNA methylome alterations. Transient transcriptomic changes not linked to DNA methylation were enriched for inflammatory and oxidative stress pathways, whereas persistent methylation-associated adaptations were related to immunomodulation and tissue remodelling. Together, this study provides insight into molecular mechanisms contributing to skeletal muscle adaptation to aerobic exercise training in sedentary individuals.

BACKGROUNDLittle is known about whether epigenetic age acceleration (EAA) clocks are capable of predicting exceptional longevity with or without preserved cognitive function. METHODSWe examined 5844 women from the Womens Health Initiative Memory Study. Fifteen epigenetic clocks were measured at baseline (1996-1999). Longevity outcomes were defined as: 1) survival to age 90 with preserved cognition (n=1726, 29.5%); or 2) survival to age 90 with cognitive impairment (n=956, 16.4%); vs. 3) death before age 90 (n=2611, 44.7%). Logistic regression models examined associations between the 15 clocks and survival to age 90 (vs. death before age 90), adjusting for covariates. Multinomial logistic regression models examined associations with survival to age 90 without cognitive impairment and survival to age 90 with cognitive impairment (each vs. death before age 90), also adjusting for covariates. FINDINGSEach standard deviation increase in EAA for the first-generation clocks was associated with 7%-18% reduced odds of survival to age 90 vs. earlier death. Stronger associations were observed for second- and third-generation clocks, including AgeAccelGrim2 (OR=0.66; 95% CI 0.61-0.71), PCGrimAge (OR=0.64; 95% CI 0.59-0.69), PCPhenoAge (OR=0.73; 95% CI 0.68-0.78) and DunedinPACE (OR= 0.77; 95% CI 0.72-0.82). None of the clocks was more strongly associated with survival to age 90 with preserved cognition than with survival to age 90 with cognitive impairment, relative to death before age 90. INTERPRETATIONAll epigenetic clocks were associated with exceptional longevity, but none were associated with cognitive healthspan. Developing clocks that can differentiate long survival with and without preserved cognitive function is critical.

BackgroundX chromosome inactivation (XCI) is the mechanism which randomly silences one X chromosome to equalise gene expression between 46, XX females and 46, XY males. Though XCI is expected to result in a random pattern of mosaicism across tissues, some females display a significantly unbalanced ratio in immune cells, termed XCI-skew, in which [&ge;]75% of cells have the same X inactivated. XCI-skew is associated with adverse health outcomes and its prevalence increases with age - particularly after midlife - yet the specific risk factors have yet to be identified. The menopausal transition, which is driven by profound shifts in sex hormone levels, has significant impact on chronic disease risk yet the molecular and cellular effects are incompletely understood. We hypothesised that the menopausal transition may impact XCI-skew. MethodsUsing XCI data measured in blood-derived DNA from 1,395 females from the TwinsUK population cohort, along with questionnaires, genetic data, and sex hormone measures, we carried out a cross-sectional study to assess the impact of the menopausal transition and sex hormones on XCI-skew. ResultsWe demonstrate that early menopause (<45yrs) is associated with increased risk of XCI-skew. In subset analyses across those who had a surgically induced or natural menopause, we find the association restricted to those who underwent a surgical menopause. We next identify a low polygenic score (PGS) for testosterone levels is significantly associated with XCI-skew, which we replicate in an independent dataset (n=149), while a PGS for age at natural menopause is not associated. Finally, using longitudinal measures across two time points spanning [~]18 years we show XCI-skew is a stable cellular phenotype that typically increases over time. DiscussionThese data represent the first environmental and genetic risk factors of XCI-skew, both of which implicate endogenous sex hormone levels, particularly testosterone. We propose XCI-skew may have clinical relevance in postmenopausal females.

BackgroundHomozygous biallelic inactivation of CDKN1B is thought to be rare in cancer. Herein we evaluate the prevalence of intratumoral (subclonal) complete p27 protein loss (IPPL) in primary prostate cancer. Experimental DesignWe used immunohistochemistry (IHC) for p27 in a large cohort of whole tissue sections from radical prostatectomy (n=412) and metastases from self-identified African American (AA) and European American (EA) individuals. IPPL was evaluated alongside CDKN1B mRNA in-situ hybridization and next generation sequencing of laser captured cancer regions. Cox proportional hazards analyses assessed the association of IPPL with biochemical recurrence and development of metastases after radical prostatectomy. ResultsIPPL was detected in 18.1% of AA versus 12.2% of EA cases and was tightly correlated with CDKN1B mRNA loss and biallelic genomic loss. IPPL was associated with [&ge;]pT3 pathologic stage and pN1 disease, however these associations were only significant among AA participants. IPPL was further associated in both univariate and multivariate analyses with the development of biochemical recurrence and metastasis after primary treatment, specifically in AA individuals. The prevalence of p27 genomic alterations in metastatic disease is higher than that of primary prostate cancer in publicly available datasets as well as our analysis of autopsy cases via IHC, indicating that complete p27 loss may be selected for in metastatic disease. ConclusionsSubclonal biallelic loss of CDKN1B resulting in complete p27 protein loss is one of the most commonly occurring biallelic tumor suppressor genomic alterations in primary prostate cancer, and could contribute to worse prostate cancer outcomes, specifically in AA males.

BackgroundWnt/{beta}-catenin signalling is dysregulated in acute myeloid leukaemia (AML), where it lacks effective targeting strategies. Previously, we discovered that {beta}-catenin interacts with several RNA-binding proteins (RBP), indicating post-transcriptional influence which is yet to be therapeutically interrogated in AML. MethodsCo-immunoprecipitation confirmed protein interactions, and TCF/LEF reporters were used to assess Wnt signalling output in leukaemia cells. Regulatory crosstalk was assessed using immunoblotting and RT-qPCR approaches following lentiviral transduction of myeloid cell lines. Targeting of {beta}-catenin and LIN28B was tested through combinations of genetic and pharmacological inhibition in AML cells. ResultsThe most frequent RBP-binding motif amongst {beta}-catenin-bound mRNAs was the GGAG motif targeted by oncofetal miRNA-regulating RBP; LIN28B. {beta}-Catenin:LIN28B interactions were detected in lymphoid and myeloid cell lines, plus primary human CD34 fetal-liver HSCs. LIN28B positively regulated Wnt signalling output through LEF1 regulation involving a post-transcriptional let7 miRNA mechanism. Further miRNA sequencing of {beta}-catenin- and LIN28B-depleted myeloid cells revealed potential cooperative and antagonistic function in miRNA regulation. Finally, dual-targeting both {beta}-catenin and LIN28B through either genetic and/or pharmacological means preferentially reduced AML cell viability. ConclusionThe {beta}-catenin:LIN28B axis could represent a novel synthetically lethal relationship in AML which could be exploited in rare subtypes where LIN28B expression becomes reactivated.

Hypothalamic-pituitary-adrenal axis (HPA axis) dysregulation is a risk factor for poor mental and physical health. Animal studies indicate that DNA methylation may be one mechanism through which stress can influence the function of the HPA axis, however human studies have not identified consistent individual loci. Machine learning can be used to develop methylation profile scores (MPSs), but this method has not yet been applied to HPA axis function. Using a novel machine learning pipeline, we developed an MPS to predict the salivary cortisol response (AUCi) to the Trier Social Stress Test (TSST) from whole blood Illumina Infinium HumanMethylation 450K BeadChip data (N = 84, mean age = 34, 49% female). The MPS was associated with the cortisol response in an independent, cross-tissue cohort (N = 53, mean age = 20, 51% female), both before ({beta} = 0.33, 95% CI [0.09, 0.54]) and after a social stressor ({beta} = 0.3, 95% CI [0.09, 0.47]). Functional characterisation revealed several immune, stress, and disease-related pathways and genes, including tolerance induction to self antigen, chronic myeloid leukemia, NR3C2, and PSMB4 (putatively causal in depression). We have developed and validated a novel epigenetic biomarker for stress reactivity, identifying a set of genomic loci where DNA methylation is associated with the cortisol response. Future research could investigate if HPA axis-related MPSs could be used alongside traditional risk factors to improve clinical risk assessment.

The DNA methylome changes with age. This is observed as both random drift, but also consistent alterations within certain genomic loci enabling the construction of precise age predictors. However, the functionality of these ageing-related modifications remains largely undefined. The CpG dinucleotide is the principal sequence target for these epigenetic DNA marks in differentiated cells. Here, for functional insight, we identified ultra-conserved CpGs (ucCpGs, n [~]167k) lacking observed sequence mutation in large-scale human whole genome datasets (>576k). ucCpGs were enriched, as expected, in lowly-methylated CpG dense loci, due to methylated cytosine hypermutability. Additionally, ucCpGs demonstrated pathogenic evidence (CADD, ClinVar), and enrichment in four-fold degenerate sites, as well as within developmental and ageing-related gene families (AP-2, HOX-L, C2H2-ZNF, etc). Extreme ucCpG clusters ([&ge;]16 ucCpGs/kb) were enriched for brain-expressed genes, as well as developmental and ageing/mortality pathways. ucCpGs also strongly co-located within ageing-related Differentially Methylated Regions (age-DMRs), highlighting Clustered Protocadherin Gamma, as well as HSPA2 and LHFPL4 genes. These findings further support that functional components of DNAm ageing are intertwined with developmental pathways.

Postpartum depression (PPD) arises during a period of profound endocrine and immune reorganisation, yet it is unclear whether women who develop PPD show distinct trajectories of immune-related DNA methylation compared to euthymic mothers. In a longitudinal cohort, women with PPD (n = 17) and healthy postpartum controls (n = 24) were followed from birth to 12 weeks postpartum, with repeated assessment of depressive symptoms and perceived stress and whole-blood sampling at 2-3 days (T0) and 12 weeks (T4) for Infinium MethylationEPIC array profiling. Healthy postpartum women showed a widespread gain in DNA methylation from T0 to T4 with strong enrichment of genes involved in neutrophil activation, chemokine signalling and interleukin-1 production, consistent with a normative immune-epigenetic down-tuning after childbirth. Women with PPD also exhibited immune-related changes, but with fewer differentially methylated CpGs and increased variance at sites that were stably hypermethylated in controls, indicating an attenuated and more heterogeneous epigenetic response. Although no CpG reached epigenome-wide significance in direct case-control contrasts, longitudinal consistency analyses highlighted a small set of CpGs with reproducible PPD-associated hypermethylation in stress- and signalling-related genes, including FKBP5 and AVP, suggesting that disrupted immune-epigenetic adaptation and altered regulation at these loci may contribute to postpartum vulnerability.

IntroductionUnderstanding the links between metabolism, ageing and age-related phenotypes may clarify the role of ageing in disease onset and improve risk prediction. MethodsWe conducted a cross-cohort assessment of biological age using broad-spectrum LC-MS metabolomics in 2,295 participants, aged 20-89, from the UK Airwave study (N=960) and The Irish Longitudinal Study of Ageing (N=1,335). ResultsN2,N2-dimethylguanosine, C-glycosyltryptophan, bile acid glucuronides, and zeta-carotene were associated with chronological age, frailty, and mortality. We developed a metabolomic clock that was highly predictive of chronological age (r = 0.92) in test samples. Metabolomic age acceleration was strongly correlated between study visits (r > 0.6). Each standard deviation higher metabolomic age acceleration ([~]5 years) was associated with 43% higher mortality risk, 27% higher risk of mild cognitive impairment, and 10% increased risk of a higher frailty score in fully adjusted models. DiscussionOur metabolomic clock provides a reproducible marker of generalised age-related disease risk.

BackgroundAdrenal steroid hormone production is essential for systemic stress adaptation and metabolic homeostasis, and it is tightly regulated by oxygen availability. Previously, we demonstrated that acute hypoxia suppresses adrenal steroidogenesis through HIF-1-dependent induction of microRNAs (miRNAs) that target key steroidogenic enzymes. However, the mechanisms by which HIF-1 controls miRNA expression and activity in this context remain unclear. MethodsTo address this issue, we mapped the genome-wide HIF-1 binding landscape in murine adrenocortical cells using Cleavage Under Targets & Tagmentation (CUT&Tag). We integrated this data with gene expression analyses following pharmacological HIF-1 stabilization, physiological hypoxia, and genetic HIF-1 depletion to distinguish HIF-1-dependent effects from broader hypoxia-driven responses. ResultsWe detected HIF-1 binding at loci encoding steroidogenic enzymes and steroidogenesis-associated miRNAs. Unexpectedly, we also detected binding at genes involved in miRNA biogenesis and function, including components of the nuclear microprocessor complex and the cytoplasmic RNA-induced silencing complex (RISC). Functional analyses revealed that hypoxia broadly represses the expression of miRNA-processing genes through both HIF-1-dependent and -independent mechanisms. Notably, HIF-1 selectively modulated or counteracted this repression in a gene-specific manner, indicating a regulatory role beyond direct transcriptional activation. ConclusionsThese findings reveal an unrecognized layer of hypoxia-driven cell communication, wherein HIF-1 coordinates the transcriptional and post-transcriptional regulation of adrenal steroidogenesis by shaping the miRNA-processing landscape. This work extends our understanding of how oxygen-sensitive signaling pathways integrate gene expression and RNA-based regulatory mechanisms to control endocrine function.