Biology subjects

Moore, A. Z.

Publications and source records attributed to Moore, A. Z..

6 recordsLinked to original sources

bioRxiv2025

The blood proteome predicts the impact of circulating factors on age-related mitochondrial health

Circulating non-cellular factors, such as plasma proteins, contribute to various features of aging. To determine the impacts of endogenous circulating factors on human age-related bioenergetic decline, we treated primary human fibroblasts with serum samples representing the adult life-course. Our results demonstrate that the maximal mitochondrial bioenergetic capacity of fibroblasts treated with serum is negatively correlated with the chronological and epigenetic age of the serum donor. Using targeted proteomics, we identified plasma proteins associated with the bioenergetic effects of serum. We then utilized elastic net, a linear regression modeling technique, to derive a novel proteomic signature of age-related mitochondrial differences. MitoAge is a 25-protein signature of age-related mitochondrial health that predicts the systemic bioenergetic effects of circulating factors and is related to differences in physical function across human aging. Signatures that report on cellular hallmarks of aging, such as mitochondrial function, represent a new generation of mechanistically-informed biomarkers of biological aging. GRAPHICAL ABSTRACTIn this study, we describe the development of a novel proteomic signature, MitoAge. This signature was developed by utilizing human primary fibroblasts treated with serum samples representing the adult human life-course and analyzing how resulting respirometry correlated with chronological age, epigenetic age, and abundance of serum proteins. Utilizing machine learning techniques, we derived a 25-protein signature which can predict bioenergetics and physical features related to aging. Application and utility of this signature may be used to identify novel drivers of health and longevity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/687483v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@905c12org.highwire.dtl.DTLVardef@18ca82forg.highwire.dtl.DTLVardef@175d397org.highwire.dtl.DTLVardef@966faa_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Characterization of DNA methylation in PBMCs and donor-matched iPSCs shows methylation is reset during stem cell reprogramming

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/627515v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@18cda69org.highwire.dtl.DTLVardef@574c4corg.highwire.dtl.DTLVardef@1522644org.highwire.dtl.DTLVardef@4e799c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG HighlightsO_LIGeneration of a population-level set of iPSC lines from healthy individuals across the lifespan C_LIO_LIAging-related features were reset based on epigenetic markers of cytosine methylation and telomere length C_LIO_LIBy comparing methQTLs in iPSC vs. their donor PBMCs, we find that detection of methQTLs reflect biological functions of different cell types C_LI DNA methylation is an important epigenetic mechanism that helps define and maintain cellular functions. It is influenced by many factors, including environmental exposures, genotype, cell type, sex, and aging. Since age is the primary risk factor for developing neurodegenerative diseases, it is important to determine if aging-related DNA methylation is retained when cells are reprogrammed to an induced Pluripotent Stem Cell (iPSC) state. Here, we selected peripheral blood mononuclear cells (PBMCs; n = 99) from a cohort of diverse and healthy individuals enrolled in the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT) study to convert to iPSCs. After reprogramming we evaluated the resulting iPSCs for DNA methylation signatures to determine if they reflect the confounding factors of age and environmental factors. We used genome-wide DNA methylation arrays in both cell types to show that the epigenetic clock is largely reset to an early methylation age after conversion of PBMCs to iPSCs. We further examined the epigenetic age of each cell type using an Epigenome-wide Association Study (EWAS). Finally, we identified a set of methylation Quantitative Trait Loci (methQTL) in each cell type. Our results show that age-related DNA methylation is largely reset in iPSCs, and each cell type has a unique set of methylation sites that are genetically influenced.

molecular biology↗

bioRxiv2024

Compatibility and comparative analysis of chronological and biological aging between the legacy 450K and the EPIC v2.0 arrays

Several different epigenetic clocks built from DNA methylation beadchip arrays, including the Illumina Infinium Human Methylation 450K and EPICv1 BeadChips, have been developed and are used to evaluate biological aging. However, there is still limited information on effectively utilizing the novel EPICv2 arrays and addressing biases in epigenetic clock calculations resulting from missing probes initially present on legacy arrays. We address how the absence of probes on the EPICv2 array, originally present on the 450K array, affects many available epigenetic clock estimates. Using data from the InCHIANTI study of aging, our findings show that while clocks like Hannum and GrimAgeV2 exhibit significant over- or underestimation due to missing probes, the correlations between estimates from all 450K probes (unreduced) and those from shared probes between 450K and EPICv2 (reduced) remain strong. In this cohort, we consider AgeAcceleration from traditional epigenetic clocks to be the most reliable approach. Their values do not significantly change upon probe reduction, with unreduced and reduced values being nearly identical and with stable mean differences across chronological age.

genetics↗

bioRxiv2023

Epigenetic signature of human immune aging: the GESTALT study.

Age-associated DNA methylation in blood cells convey information on health status. However, the mechanisms that drive these changes in circulating cells and their relationships to gene regulation are unknown. We identified age-associated DNA methylation sites in six purified blood borne immune cell types (naive B, naive CD4+and CD8+ T cells, granulocytes, monocytes and NK cells) collected from healthy individuals interspersed over a wide age range. Of the thousand of age-associated sites, only 350 sites were differentially methylated in the same direction in all cell types and validated in an independent longitudinal cohort. Genes close to age-associated hypomethylated sites were enriched for collagen biosynthesis and complement cascade pathways, while genes close to hypermethylated sites mapped to neuronal pathways. In-silico analyses showed that in most cell types, the age-associated hypo- and hypermethylated sites were enriched for ARNT (HIF1{beta}) and REST transcription factor motifs respectively, which are both master regulators of hypoxia response. To conclude, despite spatial heterogeneity, there is a commonality in the putative regulatory role with respect to transcription factor motifs and histone modifications at and around these sites. These features suggest that DNA methylation changes in healthy aging may be adaptive responses to fluctuations of oxygen availability.

molecular biology↗

bioRxiv2021

A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking

Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data. Unfortunately, measurements for individual CpGs can be surprisingly unreliable due to technical noise, and this may limit the utility of epigenetic clocks. We report that noise produces deviations up to 3 to 9 years between technical replicates for six major epigenetic clocks. The elimination of low-reliability CpGs does not ameliorate this issue. Here, we present a novel computational multi-step solution to address this noise, involving performing principal component analysis on the CpG-level data followed by biological age prediction using principal components as input. This method extracts shared systematic variation in DNAm while minimizing random noise from individual CpGs. Our novel principal-component versions of six clocks show agreement between most technical replicates within 0 to 1.5 years, equivalent or improved prediction of outcomes, and more stable trajectories in longitudinal studies and cell culture. This method entails only one additional step compared to traditional clocks, does not require prior knowledge of CpG reliabilities, and can improve the reliability of any existing or future epigenetic biomarker. The high reliability of principal component-based epigenetic clocks will make them particularly useful for applications in personalized medicine and clinical trials evaluating novel aging interventions.

bioinformatics↗

bioRxiv2018

Novel DNA methylation sites of glucose and insulin homeostasis: an integrative cross-omics analysis

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of the functional relevance of the phenomenon remains limited. Because obesity is the main risk factor for T2D and a driver of methylation from previous study, we aimed to explore the effect of DNA methylation in the early phases of T2D pathology while accounting for body mass index (BMI). We performed a blood-based epigenome-wide association study (EWAS) of fasting glucose and insulin among 4,808 non-diabetic European individuals and replicated the findings in an independent sample consisting of 11,750 non-diabetic subjects. We integrated blood-based in silico cross-omics databases comprising genomics, epigenomics and transcriptomics collected by BIOS project of the Biobanking and BioMolecular resources Research Infrastructure of the Netherlands (BBMRI-NL), the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium, and the tissue-specific Genotype-Tissue Expression (GTEx) project. We identified and replicated nine novel differentially methylated sites in whole blood (P-value < 1.27 x 10-7): sites in LETM1, RBM20, IRS2, MAN2A2 genes and 1q25.3 region were associated with fasting insulin; sites in FCRL6, SLAMF1, APOBEC3H genes and 15q26.1 region were associated with fasting glucose. The association between SLAMF1, APOBEC3H and 15q26.1 methylation sites and glucose emerged only when accounted for BMI. Follow-up in silico cross-omics analyses indicate that the cis-acting meQTLs near SLAMF1 and SLAMF1 expression are involved in glucose level regulation. Moreover, our data suggest that differential methylation in FCRL6 may affect glucose level and the risk of T2D by regulating FCLR6 expression in the liver. In conclusion, the present study provided nine new DNA methylation sites associated with glycemia homeostasis and also provided new insights of glycemia related loci into the genetics, epigenetics and transcriptomics pathways based on the integration of cross-omics data in silico.

genomics↗