Biology subjects

Marioni, R.

Publications and source records attributed to Marioni, R..

16 recordsLinked to original sources

bioRxiv2026

Increased stress in early life epigenetically rewires pathways related to aging and longevity

Environmental conditions experienced early in life have profound consequences for vertebrate health, yet the molecular pathways linking developmental stress to aging and reduced lifespan remain poorly understood. Through a novel highly accurate epigenetic clock, developed from RRBS-based blood DNA methylation profiles, we show that experimental lifespan-reducing early-life stress rapidly accelerates epigenetic age in zebra finch chicks (Taeniopygia guttata). Corticosterone-treated 29-day-old chicks share differentially methylated loci with non-treated aged birds and cluster with 6-month-old birds. The transcriptional repressor ZBTB16 emerges as an epigenetically top age-correlated gene and is strongest affected by corticosterone. Elevated developmental corticosterone causes rapid epigenetic remodelling of metabolic pathways well-established in aging and longevity. Our results demonstrate epigenetic rewiring of the aging trajectory through conserved stress-survival mechanisms immediately following elevated early-life stress exposure.

developmental biology↗

bioRxiv2026

Joint Variable Selection for Omic Biomarkers in Time-to-Event Data

The incidence of the vast majority of neurodegenerative, cancer, and metabolic diseases generally increases exponentially with age. In large-scale biobanks, linking time-to-diagnosis information in electronic health records to multiple genomic ("multiomics") measures has the potential to reveal the genes and biological pathways involved in the disease onset and progression. To date, association testing has commonly been conducted by testing one variable at a time using semiparametric Cox proportional hazards (CoxPH) models, which ignores correlation structure and increases the risk of false discoveries. To address these issues, we introduce a novel fully parametric Bayesian computational method, vampW, based on the Vector Approximate Message Passing framework applied to a Weibull model. vampW jointly models correlated features, while providing an interpretable hazard structure, producing a continuous survival curve, and incorporating prior knowledge. In an extensive simulation study, we demonstrate that joint modeling of omics data and time-to-event outcomes with vampW, substantially reduces false discoveries in comparison to marginal testing and other forms of joint CoxPH models. In 53,018 individuals from the UK Biobank, vampW identifies 219 protein associations with 24 disease outcomes, most of which are not among the top marginal discoveries. We further correct protein levels for exponential age effects, identifying 1,308 associations and highlighting the sensitivity of the analysis to age-correction methodology. Our findings replicate in independent cohorts using different measurement technologies, within data from Iceland and a novel Generation Scotland proteomics dataset. vampW also achieves significant improvement in the prediction of disease onset times: across 14 outcomes, it reduces the root mean squared error by over 32% and 26%, when compared to CoxPH variants and the deep learning approach DeepSurv, respectively, while maintaining predictive utility in minority populations. In summary, vampW offers accurate and interpretable variable selection and out-of-sample prediction within a single computational framework, making it a powerful tool for dissecting the genomic architecture of common complex disease onset.

bioinformatics↗

bioRxiv2025

Clinical progression of clonal hematopoiesis is determined by a combination of mutation timing, fitness, and clonal structure

Clonal hematopoiesis (CH) is characterized by expanding blood cell clones carrying somatic mutations in healthy aged individuals and is associated with various age-related diseases and all-cause mortality. While CH mutations affect diverse genes associated with myeloid malignancies, their mechanisms of expansion and disease associations remain poorly understood. We investigate the relationship between clonal fitness and clinical outcomes by integrating data from three longitudinal aging cohorts (n=713, observations=2,341). We demonstrate pathway-specific fitness advantage and clonal composition influence clonal dynamics. Further, the timing of mutation acquisition is necessary to determine the extent of clonal expansion reached during the host individuals lifetime. We introduce MACS120, a metric combining mutation context, timing, and variant fitness to predict future clonal growth, outperforming traditional variant allele frequency measurements in predicting clinical outcomes. Our unified analytical framework enables standardized clonal dynamics inference across cohorts, advancing our ability to predict and potentially intervene in CH-related pathologies.

genetics↗

bioRxiv2024

Imputed DNA methylation outperforms measured loci associations with smoking and chronological age

Multi-locus signatures of blood-based DNA methylation are well-established biomarkers for lifestyle and health outcomes. Here, we focus on two CpGs that are strongly associated with age and smoking behaviour. Imputing these loci via epigenome-wide CpGs results in stronger associations with outcomes in external datasets compared to directly measured CpGs. If extended epigenome-wide, CpG imputation could augment historic arrays and recently-released, inexpensive but lower-content arrays, thereby yielding better-powered association studies.

genetics↗

bioRxiv2023

isGWAS: ultra-high-throughput, scalable and equitable inference of genetic associations with disease

Genome-wide association studies (GWAS) have proven a powerful tool for human geneticists to generate biological insights or hypotheses for drug discovery. Nevertheless, a dependency on sensitive individual-level data together with ever-increasing cohort sample sizes, numbers of variants and phenotypes studied put a strain on existing algorithms, limiting the GWAS approach from maximising potential. Here we present in-silico GWAS (isGWAS), a uniquely scalable algorithm to infer regression parameters in case-control GWAS from cohort-level summary data. For any sample size, isGWAS computes a variant-disease association parameter in [~]1 millisecond, or [~]11m variants in UK-Biobank within [~]4 minutes ([~]1500-fold faster than state-of-the-art). Extensive simulations and empirical tests demonstrate that isGWAS results are highly comparable to traditional regression-based approaches. We further introduce a heuristic re-sampling algorithm, leapfrog re-sampler (LRS), to extrapolate association results to semi-virtually enlarged cohorts. Owing to significant computational gains we anticipate a broad use of isGWAS and LRS which are customizable on a web interface.

genetics↗

bioRxiv2021

Characterizing the human methylome across the life course: findings from eight UK-based studies

Variation in DNA methylation (DNAm) is associated with multiple biological processes that track growth and development, ageing and age-related diseases. However, there is little understanding of what constitutes typical patterns of DNAm variation and how these patterns change across the life course. In this study, we synthesised a map of the human methylome across the life course, focussing on changes in variability and mean DNAm. Harmonizing DNAm datasets across eight longitudinal and cross-sectional UK-based studies, we meta-analysed n=13,215 blood samples from n=7,037 unique individuals from birth to 98 years of age. Changes in CpG-specific variability and means were described across the life course using a meta-regression framework. CpG-specific associations of variability or mean DNAm in relation to the likelihood of association with 100 traits linked to environmental exposures, health and disease were tested within and across ten developmental age bins across the life course. Age was linked to DNAm variability at 29,212 CpG sites. On average, we observed a 1.26 fold increase in DNAm variability per year across the life course. 33,730 CpGs displayed changes in mean DNAm, with 64% of these loci showing decreases in DNAm over time. CpG sites linked to traits were in general more variable across the life course. Our study provides, for the first time, a map of the human methylome across the life course, which is publicly accessible through a searchable online database. This resource allows researchers to query CpG-specific trajectories from birth to old age and link these to health and disease.

genetics↗

bioRxiv2020

Methylation-Based Age Estimation in a Wild Mouse

The age structure of populations, or the ageing rate of individuals, impacts aspects of ecology, epidemiology and conservation. Yet for many wild organisms, age is an inaccessible trait. In many cases measuring age or ageing rates in the wild requires molecular biomarkers of age. Epigenetic clocks based on DNA methylation have been shown to accurately estimate the age of humans and laboratory mice, but they also show variable ticking rates that are associated with mortality risk above and beyond that predicted by chronological age. Thus, epigenetic clocks are proving to be useful markers of both chronological and biological age, and they are beginning to be applied to wild mammals and birds. We have acquired strong evidence that an accurate clock is possible for the wood mouse Apodemus sylvaticus by adapting epigenetic information from the laboratory mouse (Mus musculus). Apodemus sylvaticus is a well-studied, common small mammal in the UK and Europe, which is amenable to large-scale experimental perturbations and longitudinal sampling of individuals across their lives. These features of the wood mouse system offer opportunities to disentangle causal relationships between ageing rates and environmental stress. Our wood mouse epigenetic clock is PCR-based, and so requires only tiny amounts of tissue accessible through non-destructive sampling. We quantified methylation using Oxford Nanopore sequencing technology and present a new bioinformatics pipeline for data analysis. We thus describe a new and generalizable system that should enable ecologists and other field biologists to go from small tissue samples to an epigenetic clock for their study animal, which will enable investigations of ageing in the wild which where previously inaccessible.

genetics↗

bioRxiv2019

Assessment of DNA methylation differences between carriers of APOE ε4 and APOE ε2

BACKGROUNDThe Apolipoprotein E (APOE) {varepsilon}4 allele is the strongest genetic risk factor for late onset Alzheimers disease, while the {varepsilon}2 allele confers protection. Previous studies report differential DNA methylation of APOE between {varepsilon}4 and {varepsilon}2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODSUsing the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimers disease-free APOE {varepsilon}4 (n=2469) and {varepsilon}2 (n=1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTSWe obtained replicated evidence for DNA methylation differences in a ~169kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 x 10-100[≤]P[≤]2.44 x 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 x 10-4[≤]P[≤]3.01 x 10-2). Pathway and meQTL analyses implicated lipid-related processes and high density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONSAPOE {varepsilon}4 vs. {varepsilon}2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

genetics↗

bioRxiv2019

Age-related clonal haemopoiesis is associated with increased epigenetic age

Age-related clonal haemopoiesis (ARCH) in healthy individuals was initially observed through an increased skewing in X chromosome inactivation. More recently, several groups reported that ARCH is driven by somatic mutations. The most prevalent ARCH mutations are in the DNMT3A and TET2 genes, previously described as drivers of myeloid malignancies. ARCH is associated with an increased risk for haematological cancers. ARCH also confers an increased risk for non-haematological diseases such as cardiovascular disease, atherosclerosis, and chronic ischemic heart failure, for which age is a main risk factor. Whether ARCH is linked to accelerated ageing has remained unexplored. The most accurate and commonly-used tools to measure age acceleration are epigenetic clocks. They are based on age-related methylation differences at specific CpG sites correlating chronological age accurately with epigenetic age. Deviations from chronological age towards an increased epigenetic age have been associated with increased risk of earlier mortality and age-related morbidities. Here we present evidence of accelerated epigenetic age in individuals with ARCH.

bioinformatics↗

bioRxiv2019

A meta-analysis of genome-wide association studies of epigenetic age acceleration

Epigenetic age acceleration is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with fathers age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.\n\nAuthor SummaryDNA methylation, a type of epigenetic process, is known to vary with age. Methylation levels at specific sites across the genome can be combined to form estimates of age known as epigenetic age. The difference between epigenetic age and chronological age is referred to as epigenetic age acceleration, with positive values indicating that a person is biologically older than their years. Understanding why some people seem to age faster than others could shed light on the biological processes behind age-related decline; however, the mechanisms underlying differential rates of epigenetic ageing are largely unknown. Here, we investigate genetic determinants of two commonly used epigenetic age acceleration measures, based on the Horvath and Hannum epigenetic clocks. We report novel genetic variants and genes associated with epigenetic age acceleration, and highlight differences in the genetic factors influencing these two measures. We identify ten genetic variants and 21 genes associated with Horvath-based epigenetic age acceleration, and one variant and 12 genes associated with the Hannum-based measure. There were no genome-wide significant variants or genes in common between the Horvath-based and Hannum-based measures, supporting the hypothesis that they represent different aspects of ageing. Our results suggest a partial genetic basis underlying some previously reported phenotypic associations.

genetics↗

bioRxiv2018

Improved prediction of chronological age from DNA methylation limits it as a biomarker of ageing

DNA methylation is associated with age. The deviation of age predicted from DNA methylation from actual age has been proposed as a biomarker for ageing. However, a better prediction of chronological age implies less opportunity for biological age. Here we used 13,661 samples (from blood and saliva) in the age range of 2 to 104 years from 14 cohorts measured on Illumina HumanMethylation450/EPIC arrays to perform prediction analyses. We show that increasing the sample size achieves a smaller prediction error and higher correlations in test datasets. We demonstrate that smaller prediction errors provide a limit to how much variation in biological ageing can be captured by methylation and provide evidence that age predictors from small samples are prone to confounding by cell composition. Our predictor shows a similar or better performance in non-blood tissues including saliva, endometrium, breast, liver, adipose and muscle, compared with Horvaths across-tissue age predictor.

bioinformatics↗

bioRxiv2018

Partial reprogramming induces a steady decline in epigenetic age before loss of somatic identity

Induced pluripotent stem cells (IPSCs), with their unlimited regenerative capacity, carry the promise for tissue replacement to counter age-related decline. However, attempts to realise in vivo iPSC have invariably resulted in the formation of teratomas. Partial reprogramming in prematurely aged mice has shown promising results in alleviating age-related symptoms without teratoma formation. Does partial reprogramming lead to rejuvenation (i.e. \"younger\" cells), rather than dedifferentiation, which bears the risk of cancer? Here we analyse the dynamics of cellular age during human iPSC reprogramming and find that partial reprogramming leads to a reduction in the epigenetic age of cells. We also find that the loss of somatic gene expression and epigenetic age follow different kinetics, suggesting that they can be uncoupled and there could be a safe window where rejuvenation can be achieved with a minimised risk of cancer.

developmental biology↗

bioRxiv2018

GWAS on family history of Alzheimer’s disease

Alzheimers disease (AD) is a public health priority for the 21st century. Risk reduction currently revolves around lifestyle changes with much research trying to elucidate the biological underpinnings. Using self-report of parental history of Alzheimers dementia for case ascertainment in a genome-wide association study of over 300,000 participants from UK Biobank (32,222 maternal cases, 16,613 paternal cases) and meta-analysing with published consortium data (n=74,046 with 25,580 cases across the discovery and replication analyses), six new AD-associated loci (P<5x10-8) are identified. Three contain genes relevant for AD and neurodegeneration: ADAM10, ADAMTS4, and ACE. Suggestive loci include drug targets such as VKORC1 (warfarin dose) and BZRAP1 (benzodiazepine receptor). We report evidence that association of SNPs and AD at the PVR gene is potentially mediated by both gene expression and DNA methylation in the prefrontal cortex. Our discovered loci may help to elucidate the biological mechanisms underlying AD and, given that many are existing drug targets for other diseases and disorders, warrant further exploration for potential precision medicine applications.

genetics↗

bioRxiv2017

Epigenetic influences on aging: a longitudinal genome-wide methylation study in old Swedish twins

Age-related changes in DNA methylation have been observed in many cross-sectional studies, but longitudinal evidence is still very limited. Here, we aimed to characterize longitudinal age-related methylation patterns (Illumina HumanMethylation450 array) using 1011 blood samples collected from 385 old Swedish twins (mean age of 69 at baseline) up to five times over 20 years. We identified 1316 age-associated methylation sites (p<1.3x10-7) using a longitudinal epigenome-wide association study design. We measured how estimated cellular compositions changed with age and how much they confounded the age effect. We validated the results in two independent longitudinal cohorts, where 118 CpGs were replicated in PIVUS (p<3.9x10-5) and 594 were replicated in LBC (p<5.1x10-5). Functional annotation of age-associated CpGs showed enrichment in CCCTC-binding factor (CTCF) and other unannotated transcription factor binding sites. We further investigated genetic influences on methylation (methylation quantitative trait loci) and found no interaction between age and genetic effects in the 1316 age-associated CpGs. Moreover, in the same CpGs, methylation differences within twin pairs increased over time, where monozygotic twins had smaller intra-pair differences than dizygotic twins. We show that age-related methylation changes persist in a longitudinal perspective, and are fairly stable across cohorts. Moreover, the changes are under genetic influence, although this effect is independent of age. In addition, inter-individual methylation variations increase over time, especially in age-associated CpGs, indicating the increase of environmental contributions on DNA methylation with age.

genetics↗

bioRxiv2017

Accelerated Epigenetic Ageing in Major Depressive Disorder

BackgroundMajor depressive disorder (MDD) is a severe, heritable psychiatric disorder associated with shortened lifespan and comorbidities of advancing age. It is unknown however whether MDD is associated with accelerated biological ageing relative to chronological age. This hypothesis was tested using the epigenetic clock as a measure of biological age.\n\nMethodsTo address the main hypothesis, using peripheral blood, we derived measures of Epigenetic Age Acceleration (EAA) in 3,833 controls and 1,219 MDD cases based on Hannum and Horvath epigenetic clocks in Generation Scotland (GS:SFHS, mean age 48 years, std dev 14.5). Models controlled for relatedness, sex, cell counts, and processing batch (basic model), as well as additional covariates of smoking and drinking status, and body mass index (BMI) (full models).\n\nResultsAccelerated epigenetic ageing was found in MDD cases versus controls using the Horvath clock ({beta}=0.0804, p=0.012 equivalent to 0.20 years) in both the basic and full models. Significant MDD*age interactions indicated greatest effects at younger age ranges. No significant differences were observed for the Hannum clock. BMI was the only additional covariate found to attenuate the relationship between EAAHorvath and MDD. Further, genetic correlation analysis indicated significant overlap in the genetic aetiology of EAAHorvath with BMI (rG=0.20, p=0.03), between MDD with BMI (rG=0.10, p=9.86x10-6), but not between EAAHorvath and MDD (rG=0.14, p=0.125). Mediation analysis indicated partial mediation of the relationship between EAAHorvath and depression status through BMI ({beta} =0.0028; p=0.0248, ~13%).\n\nConclusionThese data imply that accelerated biological ageing is associated with MDD and partially mediated through BMI.

genomics↗

bioRxiv2017

116 independent genetic variants influence the neuroticism personality trait in over 329,000 UK Biobank individuals.

Neuroticism is a stable personality trait 1; twin studies report heritability between 30% and 50% 2, and SNP-based heritability is about 15% 3. Higher levels of neuroticism are associated with poorer mental and physical health 4,5, and the economic burden of neuroticism for societies is high 6. To date, genome-wide association (GWA) studies of neuroticism have identified up to 11 genetic loci 3,7. Here we report 116 significant independent genetic loci from a GWA of neuroticism in 329,821 UK Biobank participants, with replication available in a GWA meta-analysis of neuroticism in 122,867 individuals. Genetic signals for neuroticism were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (rg = .82, SE=.03), major depressive disorder (rg = .69, SE=.07) and subjective wellbeing (rg = -.68, SE=.03) alongside other mental health traits. These discoveries significantly advance our understanding of neuroticism and its association with major depressive disorder.

genetics↗