•An epigenetic age prediction tool for blood was developed based on MPS, and the DNA methylation levels of 13 markers.•Random forest regression (RFR) was used for marker selection and model ...building.•A training set of 208 and test set of 104 whole blood samples were used for model training and evaluation.•The test set resulted in a RMSE of 3.93 years and a mean absolute deviation (MAD) of 3.16 years.•The presence of SNPs may influence DNA methylation levels and can interfere with age prediction.
The use of DNA methylation (DNAm) to obtain additional information in forensic investigations showed to be a promising and increasing field of interest. Prediction of the chronological age based on age-dependent changes in the DNAm of specific CpG sites within the genome is one such potential application. Here we present an age-prediction tool for whole blood based on massive parallel sequencing (MPS) and a random forest machine learning algorithm. MPS allows accurate DNAm determination of pre-selected markers and neighboring CpG-sites to identify the best age-predictive markers for the age-prediction tool. 15 age-dependent markers of different loci were initially chosen based on publicly available 450K microarray data, and 13 finally selected for the age tool based on MPS (DDO, ELOVL2, F5, GRM2, HOXC4, KLF14, LDB2, MEIS1-AS3, NKIRAS2, RPA2, SAMD10, TRIM59, ZYG11A). Whole blood samples of 208 individuals were used for training of the algorithm and a further 104 individuals were used for model evaluation (age 18–69). In the case of KLF14, LDB2, SAMD10, and GRM2, neighboring CpG sites and not the initial 450K sites were chosen for the final model. Cross-validation of the training set leads to a mean absolute deviation (MAD) of 3.21 years and a root-mean square error (RMSE) of 3.97 years. Evaluation of model performance using the test set showed a comparable result (MAD 3.16 years, RMSE 3.93 years). A reduced model based on only the top 4 markers (ELOVL2, F5, KLF14, and TRIM59) resulted in a RMSE of 4.19 years and MAD of 3.24 years for the test set (cross validation training set: RMSE 4.63 years, MAD 3.64 years). The amplified region was additionally investigated for occurrence of SNPs in case of an aberrant DNAm result, which in some cases can be an indication for a deviation in DNAm.
Our approach uncovered well-known DNAm age-dependent markers, as well as additional new age-dependent sites for improvement of the model, and allowed the creation of a reliable and accurate epigenetic tool for age-prediction without restriction to a linear change in DNAm with age.
Isocitrate dehydrogenase 1 (IDH1) is mutated in various types of human cancer to IDH1(R132H), a structural alteration that leads to catalysis of α-ketoglutarate to the oncometabolite ...D-2-hydroxyglutarate. In this study, we present evidence that small-molecule inhibitors of IDH1(R132H) that are being developed for cancer therapy may pose risks with coadministration of radiotherapy. Cancer cells heterozygous for the IDH1(R132H) mutation exhibited less IDH-mediated production of NADPH, such that after exposure to ionizing radiation (IR), there were higher levels of reactive oxygen species, DNA double-strand breaks, and cell death compared with IDH1 wild-type cells. These effects were reversed by the IDH1(R132H) inhibitor AGI-5198. Exposure of IDH1 wild-type cells to D-2-hydroxyglutarate was sufficient to reduce IDH-mediated NADPH production and increase IR sensitivity. Mechanistic investigations revealed that the radiosensitivity of heterozygous cells was independent of the well-described DNA hypermethylation phenotype in IDH1-mutated cancers. Thus, our results argue that altered oxidative stress responses are a plausible mechanism to understand the radiosensitivity of IDH1-mutated cancer cells. Further, they offer an explanation for the relatively longer survival of patients with IDH1-mutated tumors, and they imply that administration of IDH1(R132H) inhibitors in these patients may limit irradiation efficacy in this setting.
Mendelian disorders, arising from pathogenic variations within single genetic loci, often manifest as neurodevelopmental disorders (NDDs), affecting a significant portion of the pediatric population ...worldwide. These disorders are marked by atypical brain development, intellectual disabilities, and various associated phenotypic traits. Genetic testing aids in clinical diagnoses, but inconclusive results can prolong confirmation processes. Recent focus on epigenetic dysregulation has led to the discovery of DNA methylation signatures, or episignatures, associated with NDDs, accelerating diagnostic precision. Notably, TRIP12 and USP7, genes involved in the ubiquitination pathway, exhibit specific episignatures. Understanding the roles of these genes within the ubiquitination pathway sheds light on their potential influence on episignature formation. While TRIP12 acts as an E3 ligase, USP7 functions as a deubiquitinase, presenting contrasting roles within ubiquitination. Comparison of phenotypic traits in patients with pathogenic variations in these genes reveals both distinctions and commonalities, offering insights into underlying pathophysiological mechanisms. This review contextualizes the roles of TRIP12 and USP7 within the ubiquitination pathway, their influence on episignature formation, and the potential implications for NDD pathogenesis. Understanding these intricate relationships may unveil novel therapeutic targets and diagnostic strategies for NDDs.
Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of ...less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value = 1.27×10-32), PRODH with proline (P-value = 1.11×10-19), SLC16A9 with carnitine level (P-value = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value = 1.65×10-8) and 2p12 locus with valine (P-value = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.
Histone deacetylases (HDACs) are a group of enzymes that control histone deacetylation and bear potential to direct expression of large gene sets. We determined the effect of HDAC inhibitors (HDACi) ...on human monocytes and macrophages, with respect to their polarization, activation, and their capabilities of inducing endotoxin tolerance. To address the role for HDACs in macrophage polarization, we treated monocytes with HDAC3i, HDAC6i or pan-HDACi prior to polarization into M1 or M2 macrophages using IFNγ or IL-4 respectively. To study the HDAC inhibition effect on cytokine expression, macrophages were treated with HDACi prior to LPS-stimulation. TNFα, IL-6, and p40 were measured with ELISA, whereas modifications of Histone 3 and STAT1 were assessed using western blot. To address the role for HDAC3 in repeated LPS challenge induction, HDAC3i or
siRNA was added to monocytes prior to incubation with IFNγ, which were then repeatedly challenged with LPS and analyzed by means of protein analyses and transcriptional profiling. Pan-HDACi and HDAC3i reduced cytokine secretion in monocytes and M1 macrophages, whereas HDAC6i yielded no such effect. Notably, neither pan-HDACi nor HDAC3i reduced cytokine secretion in M2 macrophages. In contrast to previous reports in mouse macrophages, HDAC3i did not affect macrophage polarization in human cells. Likewise, HDAC3 was not required for IFNγ signaling or IFNβ secretion. Cytokine and gene expression analyses confirmed that IFNγ-treated macrophages consistently develop a cytokine response after LPS repeated challenge, but pretreatment with HDAC3i or
siRNA reinstates a state of tolerance reflected by general suppression of tolerizable genes, possibly through decreasing TLRs expression, and particularly TLR4/CD14. The development of endotoxin tolerance in macrophages is important to reduce exacerbated immune response and limit tissue damage. We conclude that HDAC3 is an attractive protein target to mediate macrophage reactivity and tolerance induction in inflammatory macrophages.
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic disorder characterized by disabling fatigue. Several studies have sought to identify diagnostic biomarkers, with varying ...results. Here, we innovate this process by combining both mRNA expression and DNA methylation data. We performed recursive ensemble feature selection (REFS) on publicly available mRNA expression data in peripheral blood mononuclear cells (PBMCs) of 93 ME/CFS patients and 25 healthy controls, and found a signature of 23 genes capable of distinguishing cases and controls. REFS highly outperformed other methods, with an AUC of 0.92. We validated the results on a different platform (AUC of 0.95) and in DNA methylation data obtained from four public studies on ME/CFS (99 patients and 50 controls), identifying 48 gene-associated CpGs that predicted disease status as well (AUC of 0.97). Finally, ten of the 23 genes could be interpreted in the context of the derailed immune system of ME/CFS.
Fetal alcohol spectrum disorder (FASD) encompasses neurodevelopmental disabilities and physical birth defects associated with prenatal alcohol exposure. Previously, we attempted to identify ...epigenetic biomarkers for FASD by investigating the genome-wide DNA methylation (DNAm) profiles of individuals with FASD compared to healthy controls. In this study, we generated additional gene expression profiles in a subset of our previous FASD cohort, encompassing the most severely affected individuals, to examine the functional integrative effects of altered DNAm status on gene expression. We identified six differentially methylated regions (annotated to the
,
,
,
,
and
genes) associated with changes in gene expression (
-value < 0.05). To the best of our knowledge, this study is the first to assess whole blood gene expression and DNAm-gene expression associations in FASD. Our results present novel insights into the molecular footprint of FASD in whole blood and opens opportunities for future research into multi-omics biomarkers for the diagnosis of FASD.
Individuals with nonalcoholic fatty liver disease (NAFLD) have an altered gut microbiota composition. Moreover, hepatic DNA methylation may be altered in the state of NAFLD. Using a fecal microbiota ...transplantation (FMT) intervention, we aimed to investigate whether a change in gut microbiota composition relates to altered liver DNA methylation in NAFLD. Moreover, we assessed whether plasma metabolite profiles altered by FMT relate to changes in liver DNA methylation. Twenty-one individuals with NAFLD underwent three 8-weekly vegan allogenic donor (n = 10) or autologous (n = 11) FMTs. We obtained hepatic DNA methylation profiles from paired liver biopsies of study participants before and after FMTs. We applied a multi-omics machine learning approach to identify changes in the gut microbiome, peripheral blood metabolome and liver DNA methylome, and analyzed cross-omics correlations. Vegan allogenic donor FMT compared to autologous FMT induced distinct differential changes in I) gut microbiota profiles, including increased abundance of Eubacterium siraeum and potential probiotic Blautia wexlerae; II) plasma metabolites, including altered levels of phenylacetylcarnitine (PAC) and phenylacetylglutamine (PAG) both from gut-derived phenylacetic acid, and of several choline-derived long-chain acylcholines; and III) hepatic DNA methylation profiles, most importantly in Threonyl-TRNA Synthetase 1 (TARS) and Zinc finger protein 57 (ZFP57). Multi-omics analysis showed that Gemmiger formicillis and Firmicutes bacterium_CAG_170 positively correlated with both PAC and PAG. E siraeum negatively correlated with DNA methylation of cg16885113 in ZFP57. Alterations in gut microbiota composition by FMT caused widespread changes in plasma metabolites (e.g. PAC, PAG, and choline-derived metabolites) and liver DNA methylation profiles in individuals with NAFLD. These results indicate that FMTs might induce metaorganismal pathway changes, from the gut bacteria to the liver.
Abstract In youth with posttraumatic stress disorder (PTSD) non-response rates after treatment are often high. Epigenetic mechanisms such as DNA methylation (DNAm) have previously been linked to PTSD ...pathogenesis, additionally DNAm may affect response to (psychological) therapies. Besides investigating the direct link between DNAm and treatment response, it might be helpful to investigate the link between DNAm and previously associated biological mechanisms with treatment outcome. Thereby gaining a deeper molecular understanding of how psychotherapy (reflecting a change in the environment) relates to epigenetic changes and the adaptability of individuals. To date, limited research is done in clinical samples and no studies have been conducted in youth. Therefore we conducted a study in a Dutch cohort of youth with and without PTSD ( n = 87, age 8–18 years). We examined the cross-sectional and longitudinal changes of saliva-based genome-wide DNA methylation (DNAm) levels, and salivary cortisol secretion. The last might reflect possible abbreviations on the hypothalamic–pituitary– adrenal (HPA) axis. The HPA-axis is previously linked to DNAm and the development and recovery of PTSD. Youth were treated with 8 sessions of either Eye Movement Reprocessing Therapy (EMDR) or Trauma Focused Cognitive behavioral Therapy (TF-CBT). Our epigenome wide approach showed distinct methylation between treatment responders and non-responders on C18orf63 gene post-treatment. This genomic region is related to the PAX5 gene, involved in neurodevelopment and inflammation response. Additionally, our targeted approach indicated that there were longitudinal DNAm changes in successfully treated youth at the CRHR2 gene. Methylation at this gene was further correlated with cortisol secretion pre- and post-treatment. Awaiting replication, findings of this first study in youth point to molecular pathways involved in stress response and neuroplasticity to be associated with treatment response.
Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade, such as tumor necrosis factor-alpha (TNFα). Currently, there are no biomarkers to ...predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood (PBL).
DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of ADA treatment was determined using Illumina HumanMethylationEPIC BeadChip array. After 6 months, treatment response was assessed according to the European Alliance of Associations for Rheumatology (EULAR) criteria for disease activity. Patients were classified as responders (Disease Activity Score in 28 Joints (DAS28) < 3.2 or decrease of 1.2 points) or as non-responders (DAS28 > 5.1 or decrease of less than 0.6 points). Machine learning models were built through stability-selected gradient boosting to predict response prior to ADA treatment with predictor DNA methylation markers.
Of the 94 RA patients, we classified 49 and 43 patients as responders and non-responders, respectively. We were capable of differentiating responders from non-responders with a high performance (area under the curve (AUC) 0.76) using a panel of 27 CpGs. These classifier CpGs are annotated to genes involved in immunological and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology, and angiogenesis.
Our findings indicate that the DNA methylome of PBL provides discriminative capabilities in discerning responders and non-responders to ADA treatment and may therefore serve as a tool for therapy prediction.
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