Base-resolution analyses of sequence and parent-of-origin dependent DNA methylation in the mouse genome.

Differential methylation of the two parental genomes in placental mammals is essential for genomic imprinting and embryogenesis. To systematically study this epigenetic process, we have generated a base-resolution, allele-specific DNA methylation (ASM) map in the mouse genome. We find parent-of-origin dependent (imprinted) ASM at 1,952 CG dinucleotides. These imprinted CGs form 55 discrete clusters including virtually all known germline differentially methylated regions (DMRs) and 23 previously unknown DMRs, with some occurring at microRNA genes. We also identify sequence-dependent ASM at 131,765 CGs. Interestingly, methylation at these sites exhibits a strong dependence on the immediate adjacent bases, allowing us to define a conserved sequence preference for the mammalian DNA methylation machinery. Finally, we report a surprising presence of non-CG methylation in the adult mouse brain, with some showing evidence of imprinting. Our results provide a resource for understanding the mechanisms of imprinting and allele-specific gene expression in mammalian cells.

Methylomic signature of current cannabis use in two first-episode psychosis cohorts.

The rising prevalence and legalisation of cannabis worldwide have underscored the need for a comprehensive understanding of its biological impact, particularly on mental health. Epigenetic mechanisms, specifically DNA methylation, have gained increasing recognition as vital factors in the interplay between risk factors and mental health. This study aimed to explore the effects of current cannabis use and high-potency cannabis on DNA methylation in two independent cohorts of individuals experiencing first-episode psychosis (FEP) compared to control subjects. The combined sample consisted of 682 participants (188 current cannabis users and 494 never users). DNA methylation profiles were generated on blood-derived DNA samples using the Illumina DNA methylation array platform. A meta-analysis across cohorts identified one CpG site (cg11669285) in the CAVIN1 gene that showed differential methylation with current cannabis use, surpassing the array-wide significance threshold, and independent of the tobacco-related epigenetic signature. Furthermore, a CpG site localised in the MCU gene (cg11669285) achieved array-wide significance in an analysis of the effect of high-potency (THC = > 10%) current cannabis use. Pathway and regional analyses identified cannabis-related epigenetic variation proximal to genes linked to immune and mitochondrial function, both of which are known to be influenced by cannabinoids. Interestingly, a model including an interaction term between cannabis use and FEP status identified two sites that were significantly associated with current cannabis use with a nominally significant interaction suggesting that FEP status might moderate how cannabis use affects DNA methylation. Overall, these findings contribute to our understanding of the epigenetic impact of current cannabis use and highlight potential molecular pathways affected by cannabis exposure.

Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles.

BACKGROUND: Due to interindividual variation in the cellular composition of the human cortex, it is essential that covariates that capture these differences are included in epigenome-wide association studies using bulk tissue. As experimentally derived cell counts are often unavailable, computational solutions have been adopted to estimate the proportion of different cell types using DNA methylation data. Here, we validate and profile the use of an expanded reference DNA methylation dataset incorporating two neuronal and three glial cell subtypes for quantifying the cellular composition of the human cortex. RESULTS: We tested eight reference panels containing different combinations of neuronal- and glial cell types and characterised their performance in deconvoluting cell proportions from computationally reconstructed or empirically derived human cortex DNA methylation data. Our analyses demonstrate that while these novel brain deconvolution models produce accurate estimates of cellular proportions from profiles generated on postnatal human cortex samples, they are not appropriate for the use in prenatal cortex or cerebellum tissue samples. Applying our models to an extensive collection of empirical datasets, we show that glial cells are twice as abundant as neuronal cells in the human cortex and identify significant associations between increased Alzheimer's disease neuropathology and the proportion of specific cell types including a decrease in NeuNNeg/SOX10Neg nuclei and an increase of NeuNNeg/SOX10Pos nuclei. CONCLUSIONS: Our novel deconvolution models produce accurate estimates for cell proportions in the human cortex. These models are available as a resource to the community enabling the control of cellular heterogeneity in epigenetic studies of brain disorders performed on bulk cortex tissue.

Developmentally dynamic changes in DNA methylation in the human pancreas.

Development of the human pancreas requires the precise temporal control of gene expression via epigenetic mechanisms and the binding of key transcription factors. We quantified genome-wide patterns of DNA methylation in human fetal pancreatic samples from donors aged 6 to 21 post-conception weeks. We found dramatic changes in DNA methylation across pancreas development, with > 21% of sites characterized as developmental differentially methylated positions (dDMPs) including many annotated to genes associated with monogenic diabetes. An analysis of DNA methylation in postnatal pancreas tissue showed that the dramatic temporal changes in DNA methylation occurring in the developing pancreas are largely limited to the prenatal period. Significant differences in DNA methylation were observed between males and females at a number of autosomal sites, with a small proportion of sites showing sex-specific DNA methylation trajectories across pancreas development. Pancreas dDMPs were not distributed equally across the genome and were depleted in regulatory domains characterized by open chromatin and the binding of known pancreatic development transcription factors. Finally, we compared our pancreas dDMPs to previous findings from the human brain, identifying evidence for tissue-specific developmental changes in DNA methylation. This study represents the first systematic exploration of DNA methylation patterns during human fetal pancreas development and confirms the prenatal period as a time of major epigenomic plasticity.

Exploring the mediation of DNA methylation across the epigenome between childhood adversity and First Episode of Psychosis-findings from the EU-GEI study.

ABTRACT: Studies conducted in psychotic disorders have shown that DNA-methylation (DNAm) is sensitive to the impact of Childhood Adversity (CA). However, whether it mediates the association between CA and psychosis is yet to be explored. Epigenome wide association studies (EWAS) using the Illumina Infinium-Methylation EPIC array in peripheral blood tissue from 366 First-episode of psychosis and 517 healthy controls was performed. Adversity scores were created for abuse, neglect and composite adversity with the Childhood Trauma Questionnaire (CTQ). Regressions examining (I) CTQ scores with psychosis; (II) with DNAm EWAS level and (III) between DNAm and caseness, adjusted for a variety of confounders were conducted. Divide-Aggregate Composite-null Test for the composite null-hypothesis of no mediation effect was conducted. Enrichment analyses were conducted with missMethyl package and the KEGG database. Our results show that CA was associated with psychosis (Composite: OR = 1.68; p = <0.001; abuse: OR = 2.16; p < 0.001; neglect: OR = 2.27; p = <0.001). None of the CpG sites significantly mediated the adversity-psychosis association after Bonferroni correction (p < 8.1 × 10-8). However, 28, 34 and 29 differentially methylated probes associated with 21, 27, 20 genes passed a less stringent discovery threshold (p < 5 × 10-5) for composite, abuse and neglect respectively, with a lack of overlap between abuse and neglect. These included genes previously associated to psychosis in EWAS studies, such as PANK1, SPEG TBKBP1, TSNARE1 or H2R. Downstream gene ontology analyses did not reveal any biological pathways that survived false discovery rate correction. Although at a non-significant level, DNAm changes in genes previously associated with schizophrenia in EWAS studies may mediate the CA-psychosis association. These results and associated involved processes such as mitochondrial or histaminergic disfunction, immunity or neural signalling requires replication in well powered samples. The lack of overlap between mediating genes associated with abuse and neglect suggests differential biological trajectories linking CA subtypes and psychosis.

Blood-based multivariate methylation risk score for cognitive impairment and dementia.

INTRODUCTION: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection. METHODS: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts. RESULTS: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10-3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia = 2.59). DISCUSSION: Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk. HIGHLIGHTS: We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.

A comparison of feature selection methodologies and learning algorithms in the development of a DNA methylation-based telomere length estimator.

BACKGROUND: The field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine-guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the challenge of high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, our aim was to test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based telomere length (TL) estimator. We utilised both nested cross-validation and two independent test sets for the comparisons. RESULTS: We found that principal component analysis in advance of elastic net regression led to the overall best performing estimator when evaluated using a nested cross-validation analysis and two independent test cohorts. This approach achieved a correlation between estimated and actual TL of 0.295 (83.4% CI [0.201, 0.384]) on the EXTEND test data set. Contrastingly, the baseline model of elastic net regression with no prior feature reduction stage performed less well in general-suggesting a prior feature-selection stage may have important utility. A previously developed TL estimator, DNAmTL, achieved a correlation of 0.216 (83.4% CI [0.118, 0.310]) on the EXTEND data. Additionally, we observed that different DNA methylation-based TL estimators, which have few common CpGs, are associated with many of the same biological entities. CONCLUSIONS: The variance in performance across tested approaches shows that estimators are sensitive to data set heterogeneity and the development of an optimal DNA methylation-based estimator should benefit from the robust methodological approach used in this study. Moreover, our methodology which utilises a range of feature-selection approaches and ML algorithms could be applied to other biological markers and disease phenotypes, to examine their relationship with DNA methylation and predictive value.

From methylation to myelination: epigenomic and transcriptomic profiling of chronic inactive demyelinated multiple sclerosis lesions.

In the progressive phase of multiple sclerosis (MS), the hampered differentiation capacity of oligodendrocyte precursor cells (OPCs) eventually results in remyelination failure. We have previously shown that DNA methylation of Id2/Id4 is highly involved in OPC differentiation and remyelination. In this study, we took an unbiased approach by determining genome-wide DNA methylation patterns within chronically demyelinated MS lesions and investigated how certain epigenetic signatures relate to OPC differentiation capacity. We compared genome-wide DNA methylation and transcriptional profiles between chronically demyelinated MS lesions and matched normal-appearing white matter (NAWM), making use of post-mortem brain tissue (n = 9/group). DNA methylation differences that inversely correlated with mRNA expression of their corresponding genes were validated for their cell-type specificity in laser-captured OPCs using pyrosequencing. The CRISPR-dCas9-DNMT3a/TET1 system was used to epigenetically edit human-iPSC-derived oligodendrocytes to assess the effect on cellular differentiation. Our data show hypermethylation of CpGs within genes that cluster in gene ontologies related to myelination and axon ensheathment. Cell type-specific validation indicates a region-dependent hypermethylation of MBP, encoding for myelin basic protein, in OPCs obtained from white matter lesions compared to NAWM-derived OPCs. By altering the DNA methylation state of specific CpGs within the promotor region of MBP, using epigenetic editing, we show that cellular differentiation and myelination can be bidirectionally manipulated using the CRISPR-dCas9-DNMT3a/TET1 system in vitro. Our data indicate that OPCs within chronically demyelinated MS lesions acquire an inhibitory phenotype, which translates into hypermethylation of crucial myelination-related genes. Altering the epigenetic status of MBP can restore the differentiation capacity of OPCs and possibly boost (re)myelination.

Growth disrupting mutations in epigenetic regulatory molecules are associated with abnormalities of epigenetic aging.

Germline mutations in fundamental epigenetic regulatory molecules including DNA methyltransferase 3 alpha (DNMT3A) are commonly associated with growth disorders, whereas somatic mutations are often associated with malignancy. We profiled genome-wide DNA methylation patterns in DNMT3A c.2312G > A; p.(Arg771Gln) carriers in a large Amish sibship with Tatton-Brown-Rahman syndrome (TBRS), their mosaic father, and 15 TBRS patients with distinct pathogenic de novo DNMT3A variants. This defined widespread DNA hypomethylation at specific genomic sites enriched at locations annotated as genes involved in morphogenesis, development, differentiation, and malignancy predisposition pathways. TBRS patients also displayed highly accelerated DNA methylation aging. These findings were most marked in a carrier of the AML-associated driver mutation p.Arg882Cys. Our studies additionally defined phenotype-related accelerated and decelerated epigenetic aging in two histone methyltransferase disorders: NSD1 Sotos syndrome overgrowth disorder and KMT2D Kabuki syndrome growth impairment. Together, our findings provide fundamental new insights into aberrant epigenetic mechanisms, the role of epigenetic machinery maintenance, and determinants of biological aging in these growth disorders.

Can epigenetics shine a light on the biological pathways underlying major mental disorders?

A significant proportion of the global burden of disease can be attributed to mental illness. Despite important advances in identifying risk factors for mental health conditions, the biological processing underlying causal pathways to disease onset remain poorly understood. This represents a limitation to implement effective prevention and the development of novel pharmacological treatments. Epigenetic mechanisms have emerged as mediators of environmental and genetic risk factors which might play a role in disease onset, including childhood adversity (CA) and cannabis use (CU). Particularly, human research exploring DNA methylation has provided new and promising insights into the role of biological pathways implicated in the aetio-pathogenesis of psychiatric conditions, including: monoaminergic (Serotonin and Dopamine), GABAergic, glutamatergic, neurogenesis, inflammatory and immune response and oxidative stress. While these epigenetic changes have been often studied as disease-specific, similarly to the investigation of environmental risk factors, they are often transdiagnostic. Therefore, we aim to review the existing literature on DNA methylation from human studies of psychiatric diseases (i) to identify epigenetic modifications mapping onto biological pathways either transdiagnostically or specifically related to psychiatric diseases such as Eating Disorders, Post-traumatic Stress Disorder, Bipolar and Psychotic Disorder, Depression, Autism Spectrum Disorder and Anxiety Disorder, and (ii) to investigate a convergence between some of these epigenetic modifications and the exposure to known risk factors for psychiatric disorders such as CA and CU, as well as to other epigenetic confounders in psychiatry research.

Functional characterization of the schizophrenia associated gene AS3MT identifies a role in neuronal development.

Genome-wide association studies (GWAS) have identified multiple genomic regions associated with schizophrenia, although many variants reside in noncoding regions characterized by high linkage disequilibrium (LD) making the elucidation of molecular mechanisms challenging. A genomic region on chromosome 10q24 has been consistently associated with schizophrenia with risk attributed to the AS3MT gene. Although AS3MT is hypothesized to play a role in neuronal development and differentiation, work to fully understand the function of this gene has been limited. In this study we explored the function of AS3MT using a neuronal cell line (SH-SY5Y). We confirm previous findings of isoform specific expression of AS3MT during SH-SY5Y differentiation toward neuronal fates. Using CRISPR-Cas9 gene editing we generated AS3MT knockout SH-SY5Y cell lines and used RNA-seq to identify significant changes in gene expression in pathways associated with neuronal development, inflammation, extracellular matrix formation, and RNA processing, including dysregulation of other genes strongly implicated in schizophrenia. We did not observe any morphological changes in cell size and neurite length following neuronal differentiation and MAP2 immunocytochemistry. These results provide novel insights into the potential role of AS3MT in brain development and identify pathways through which genetic variation in this region may confer risk for schizophrenia.

Sites of active gene regulation in the prenatal frontal cortex and their role in neuropsychiatric disorders.

Common genetic variation appears to largely influence risk for neuropsychiatric disorders through effects on gene regulation. It is therefore possible to shed light on the biology of these conditions by testing for enrichment of associated genetic variation within regulatory genomic regions operating in specific tissues or cell types. Here, we have used the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-Seq) to map open chromatin (an index of active regulatory genomic regions) in bulk tissue, NeuN+ and NeuN- nuclei from the prenatal human frontal cortex, and tested enrichment of single-nucleotide polymorphism (SNP) heritability for five neuropsychiatric disorders (autism spectrum disorder, attention deficit hyperactivity disorder [ADHD], bipolar disorder, major depressive disorder, and schizophrenia) within these regions. We observed significant enrichment of SNP heritability for ADHD, major depressive disorder, and schizophrenia within open chromatin regions (OCRs) mapped in bulk fetal frontal cortex, and for all five tested neuropsychiatric conditions when we restricted these sites to those overlapping histone modifications indicative of enhancers (H3K4me1) or promoters (H3K4me3) in fetal brain. SNP heritability for neuropsychiatric disorders was significantly enriched in OCRs identified in fetal frontal cortex NeuN- as well as NeuN+ nuclei overlapping fetal brain H3K4me1 or H3K4me3 sites. We additionally demonstrate the utility of our mapped OCRs for prioritizing potentially functional SNPs at genome-wide significant risk loci for neuropsychiatric disorders. Our data provide evidence for an early neurodevelopmental component to a range of neuropsychiatric conditions and highlight an important role for regulatory genomic regions active within both NeuN+ and NeuN- cells of the prenatal brain.

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions.

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease.

Erasure and reestablishment of random allelic expression imbalance after epigenetic reprogramming.

Clonal level random allelic expression imbalance and random monoallelic expression provides cellular heterogeneity within tissues by modulating allelic dosage. Although such expression patterns have been observed in multiple cell types, little is known about when in development these stochastic allelic choices are made. We examine allelic expression patterns in human neural progenitor cells before and after epigenetic reprogramming to induced pluripotency, observing that loci previously characterized by random allelic expression imbalance (0.63% of expressed genes) are generally reset to a biallelic state in induced pluripotent stem cells (iPSCs). We subsequently neuralized the iPSCs and profiled isolated clonal neural stem cells, observing that significant random allelic expression imbalance is reestablished at 0.65% of expressed genes, including novel loci not found to show allelic expression imbalance in the original parental neural progenitor cells. Allelic expression imbalance was associated with altered DNA methylation across promoter regulatory regions, with clones characterized by skewed allelic expression being hypermethylated compared to their biallelic sister clones. Our results suggest that random allelic expression imbalance is established during lineage commitment and is associated with increased DNA methylation at the gene promoter.

Childhood maternal care is associated with DNA methylation of the genes for brain-derived neurotrophic factor (BDNF) and oxytocin receptor (OXTR) in peripheral blood cells in adult men and women.

In adults, reporting low and high maternal care in childhood, we compared DNA methylation in two stress-associated genes (two target sequences in the oxytocin receptor gene, OXTR; one in the brain-derived neurotrophic factor gene, BDNF) in peripheral whole blood, in a cross-sectional study (University of Basel, Switzerland) during 2007-2008. We recruited 89 participants scoring < 27 (n = 47, 36 women) or > 33 (n = 42, 35 women) on the maternal care subscale of the Parental Bonding Instrument (PBI) at a previous assessment of a larger group (N = 709, range PBI maternal care = 0-36, age range = 19-66 years; median 24 years). 85 participants gave blood for DNA methylation analyses (Sequenom(R) EpiTYPER, San Diego, CA) and cell count (Sysmex PocH-100i™, Kobe, Japan). Mixed model statistical analysis showed greater DNA methylation in the low versus high maternal care group, in the BDNF target sequence [Likelihood-Ratio (1) = 4.47; p = 0.035] and in one OXTR target sequence Likelihood-Ratio (1) = 4.33; p = 0.037], but not the second OXTR target sequence [Likelihood-Ratio (1) < 0.001; p = 0.995). Mediation analyses indicated that differential blood cell count did not explain associations between low maternal care and BDNF (estimate = -0.005, 95% CI = -0.025 to 0.015; p = 0.626) or OXTR DNA methylation (estimate = -0.015, 95% CI = -0.038 to 0.008; p = 0.192). Hence, low maternal care in childhood was associated with greater DNA methylation in an OXTR and a BDNF target sequence in blood cells in adulthood. Although the study has limitations (cross-sectional, a wide age range, only three target sequences in two genes studied, small effects, uncertain relevance of changes in blood cells to gene methylation in brain), the findings may indicate components of the epiphenotype from early life stress.

Epigenome-Wide DNA Methylation Analysis of Monozygotic Twins Discordant for Diurnal Preference.

Diurnal preference is an individual's preference for daily activities and sleep timing and is strongly correlated with the underlying circadian clock and the sleep-wake cycle validating its use as an indirect circadian measure in humans. Recent research has implicated DNA methylation as a mechanism involved in the regulation of the circadian clock system in humans and other mammals. In order to evaluate the extent of epigenetic differences associated with diurnal preference, we examined genome-wide patterns of DNA methylation in DNA from monozygotic (MZ) twin-pairs discordant for diurnal preference. MZ twins were selected from a longitudinal twin study designed to investigate the interplay of genetic and environmental factors in the development of emotional and behavioral difficulties. Fifteen pairs of MZ twins were identified in which one member scored considerably higher on the Horne-Ostberg Morningness-Eveningness Questionnaire (MEQ) than the other. Genome-wide DNA methylation patterns were assessed in twins' buccal cell DNA using the Illumina Infinium HumanMethylation450 BeadChips. Quality control and data pre-processing was undertaken using the wateRmelon package. Differentially methylated probes (DMPs) were identified using an analysis strategy taking into account both the significance and the magnitude of DNA methylation differences. Our data indicate that DNA methylation differences are detectable in MZ twins discordant for diurnal preference. Moreover, downstream gene ontology (GO) enrichment analysis on the top-ranked diurnal preference associated DMPs revealed significant enrichment of pathways that have been previously associated with circadian rhythm regulation, including cell adhesion processes and calcium ion binding.

Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population.

Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype-phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.

Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk.

BACKGROUND: The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex. RESULTS: We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02-5.61, P = 1.1E-03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status. CONCLUSIONS: Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.

Long-read transcript sequencing identifies differential isoform expression in the entorhinal cortex in a transgenic model of tau pathology.

Increasing evidence suggests that alternative splicing plays an important role in Alzheimer's disease (AD) pathology. We used long-read sequencing in combination with a novel bioinformatics tool (FICLE) to profile transcript diversity in the entorhinal cortex of female transgenic (TG) mice harboring a mutant form of human tau. Our analyses revealed hundreds of novel isoforms and identified differentially expressed transcripts - including specific isoforms of Apoe, App, Cd33, Clu, Fyn and Trem2 - associated with the development of tau pathology in TG mice. Subsequent profiling of the human cortex from AD individuals and controls revealed similar patterns of transcript diversity, including the upregulation of the dominant TREM2 isoform in AD paralleling the increased expression of the homologous transcript in TG mice. Our results highlight the importance of differential transcript usage, even in the absence of gene-level expression alterations, as a mechanism underpinning gene regulation in the development of AD neuropathology.