Methylomic profiling of cortex samples from completed suicide cases implicates a role for PSORS1C3 in major depression and suicide.

This is the final version of the article. Available from Nature Publishing Group via the DOI in this record.Major depressive disorder (MDD) represents a major social and economic health issue and constitutes a major risk factor for suicide. The molecular pathology of suicidal depression remains poorly understood, although it has been hypothesised that regulatory genomic processes are involved in the pathology of both MDD and suicidality. In this study, genome-wide patterns of DNA methylation were assessed in depressed suicide completers (n=20) and compared with non-psychiatric, sudden-death controls (n=20) using tissue from two cortical brain regions (Brodmann Area 11 (BA11) and Brodmann Area 25 (BA25)). Analyses focused on identifying differentially methylated regions (DMRs) associated with suicidal depression and epigenetic variation were explored in the context of polygenic risk scores for major depression and suicide. Weighted gene co-methylation network analysis was used to identify modules of co-methylated loci associated with depressed suicide completers and polygenic burden for MDD and suicide attempt. We identified a DMR upstream of the PSORS1C3 gene, subsequently validated using bisulfite pyrosequencing and replicated in a second set of suicide samples, which is characterised by significant hypomethylation in both cortical brain regions in MDD suicide cases. We also identified discrete modules of co-methylated loci associated with polygenic risk burden for suicide attempt, but not major depression. Suicide-associated co-methylation modules were enriched among gene networks implicating biological processes relevant to depression and suicidality, including nervous system development and mitochondria function. Our data suggest that there are coordinated changes in DNA methylation associated with suicide that may offer novel insights into the molecular pathology associated with depressed suicide completers.We are grateful to all of the patients and control subjects who contributed to this study. The authors would like to acknowledge support of the Brain and Behaviour Research Foundation through a NARSAD Young Investigator Grant to TMM and from the UK Medical Research Council (MRC) (grant number MR/K013807/1) to JM. ZK would like to acknowledge funding from the NIH grant (grant number NIMH 1R21MH094771). The Douglas Bell Canada Brain Bank is supported by the FRQS through the Quebec Network on Suicide, Mood Disorders and Related Disorders, and by Brain Canada through an infrastructure grant. We acknowledge Niamh Mullins and Professor Catherine Lewis, King’s College London, for kindly supplying us with the suicide attempt GWAS data

A Bayesian Approach for Analysis of Whole-Genome Bisulfite Sequencing Data Identifies Disease-Associated Changes in DNA Methylation

DNA methylation is a key epigenetic modification involved in gene regulation whose contribution to disease susceptibility remains to be fully understood. Here, we present a novel Bayesian smoothing approach (called ABBA) to detect differentially methylated regions (DMRs) from whole-genome bisulfite sequencing (WGBS). We also show how this approach can be leveraged to identify disease-associated changes in DNA methylation, suggesting mechanisms through which these alterations might affect disease. From a data modeling perspective, ABBA has the distinctive feature of automatically adapting to different correlation structures in CpG methylation levels across the genome while taking into account the distance between CpG sites as a covariate. Our simulation study shows that ABBA has greater power to detect DMRs than existing methods, providing an accurate identification of DMRs in the large majority of simulated cases. To empirically demonstrate the method’s efficacy in generating biological hypotheses, we performed WGBS of primary macrophages derived from an experimental rat system of glomerulonephritis and used ABBA to identify >1000 disease-associated DMRs. Investigation of these DMRs revealed differential DNA methylation localized to a 600 bp region in the promoter of the Ifitm3 gene. This was confirmed by ChIP-seq and RNA-seq analyses, showing differential transcription factor binding at the Ifitm3 promoter by JunD (an established determinant of glomerulonephritis), and a consistent change in Ifitm3 expression. Our ABBA analysis allowed us to propose a new role for Ifitm3 in the pathogenesis of glomerulonephritis via a mechanism involving promoter hypermethylation that is associated with Ifitm3 repression in the rat strain susceptible to glomerulonephritis

Attenuated Induction of the Unfolded Protein Response in Adult Human Primary Astrocytes in Response to Recurrent Low Glucose

This is the final version. Available on open access from Frontiers Media via the DOI in this record. The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.AIMS/HYPOTHESIS: Recurrent hypoglycaemia (RH) is a major side-effect of intensive insulin therapy for people with diabetes. Changes in hypoglycaemia sensing by the brain contribute to the development of impaired counterregulatory responses to and awareness of hypoglycaemia. Little is known about the intrinsic changes in human astrocytes in response to acute and recurrent low glucose (RLG) exposure. METHODS: Human primary astrocytes (HPA) were exposed to zero, one, three or four bouts of low glucose (0.1 mmol/l) for three hours per day for four days to mimic RH. On the fourth day, DNA and RNA were collected. Differential gene expression and ontology analyses were performed using DESeq2 and GOseq, respectively. DNA methylation was assessed using the Infinium MethylationEPIC BeadChip platform. RESULTS: 24 differentially expressed genes (DEGs) were detected (after correction for multiple comparisons). One bout of low glucose exposure had the largest effect on gene expression. Pathway analyses revealed that endoplasmic-reticulum (ER) stress-related genes such as HSPA5, XBP1, and MANF, involved in the unfolded protein response (UPR), were all significantly increased following low glucose (LG) exposure, which was diminished following RLG. There was little correlation between differentially methylated positions and changes in gene expression yet the number of bouts of LG exposure produced distinct methylation signatures. CONCLUSIONS/INTERPRETATION: These data suggest that exposure of human astrocytes to transient LG triggers activation of genes involved in the UPR linked to endoplasmic reticulum (ER) stress. Following RLG, the activation of UPR related genes was diminished, suggesting attenuated ER stress. This may be a consequence of a successful metabolic adaptation, as previously reported, that better preserves intracellular energy levels and a reduced necessity for the UPR.Diabetes UKJDRF postdoctoral fellowshipMedical Research Council (MRC)Wellcome TrustBiotechnology & Biological Sciences Research Council (BBSRC)Novo Nordisk UK Research FoundationMary Kinross Charitable TrustEuropean Foundation for the Study of Diabetes/Novo Nordisk Programm

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

This is the final version. Available from Wiley via the DOI in this record. DATA AVAILABILITY STATEMENT: All raw RNAseq files are available at GSE182157 and generated cell lines available on request.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.Academy of Medical SciencesBiotechnology and Biological Sciences Research CouncilMedical Research CouncilMedical Research CouncilWellcome TrustWellcome TrustUniversity of Exete

Novel epigenetic clock for fetal brain development predicts prenatal age for cellular stem cell models and derived neurons

Induced pluripotent stem cells (iPSCs) and their differentiated neurons (iPSC-neurons) are a widely used cellular model in the research of the central nervous system. However, it is unknown how well they capture age-associated processes, particularly given that pluripotent cells are only present during the earliest stages of mammalian development. Epigenetic clocks utilize coordinated age-associated changes in DNA methylation to make predictions that correlate strongly with chronological age. It has been shown that the induction of pluripotency rejuvenates predicted epigenetic age. As existing clocks are not optimized for the study of brain development, we developed the fetal brain clock (FBC), a bespoke epigenetic clock trained in human prenatal brain samples in order to investigate more precisely the epigenetic age of iPSCs and iPSC-neurons. The FBC was tested in two independent validation cohorts across a total of 194 samples, confirming that the FBC outperforms other established epigenetic clocks in fetal brain cohorts. We applied the FBC to DNA methylation data from iPSCs and embryonic stem cells and their derived neuronal precursor cells and neurons, finding that these cell types are epigenetically characterized as having an early fetal age. Furthermore, while differentiation from iPSCs to neurons significantly increases epigenetic age, iPSC-neurons are still predicted as being fetal. Together our findings reiterate the need to better understand the limitations of existing epigenetic clocks for answering biological research questions and highlight a limitation of iPSC-neurons as a cellular model of age-related diseases

Uncertainty quantification of reference-based cellular deconvolution algorithms

This is the final version. Available on open access from Routledge via the DOI in this recordData and code availability: The DNAm data used in this study are available as R packages or via GEO (see Supplementary Table 2 for details). We have provided the code for calculating the CETYGO score as an R package available via GitHub (https://github.com/ds420/CETYGO). The code to reproduce the analyses in this manuscript using our R package are also available via GitHub (https://github.com/ejh243/CETYGOAnalyses).The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample's DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).Biotechnology and Biological Sciences Research Council (BBSRC)Engineering and Physical Sciences Research Council (EPSRC)Medical Research Council (MRC)Alzheimer’s Societ

Logical abilities and behavior in strategic-form games

This paper investigates the impact of cognitive abilities and preferences on behavior in games. We first measure subjects’ logical abilities and social preferences and then evaluate their influence on behavior in strategic-form games. For this purpose, we estimate how logical abilities and preferences relate to the probability of a subject being of a specific behavioral type. We find that better logical abilities increase the likelihood of sophisticated behavior. This shift is stronger for subjects who are classified as “selfish”. However, not even the most logically able, selfish subjects are identified as Nash types

Genome-wide DNA methylation meta-analysis in the brains of suicide completers

This is the final version. Available from Springer Nature via the DOI in this record. Suicide is the second leading cause of death globally among young people representing a significant global health burden. Although the molecular correlates of suicide remains poorly understood, it has been hypothesised that epigenomic processes may play a role. The objective of this study was to identify suicide-associated DNA methylation changes in the human brain by utilising previously published and unpublished methylomic datasets. We analysed prefrontal cortex (PFC, n = 211) and cerebellum (CER, n = 114) DNA methylation profiles from suicide completers and non-psychiatric, sudden-death controls, meta-analysing data from independent cohorts for each brain region separately. We report evidence for altered DNA methylation at several genetic loci in suicide cases compared to controls in both brain regions with suicide-associated differentially methylated positions enriched among functional pathways relevant to psychiatric phenotypes and suicidality, including nervous system development (PFC) and regulation of long-term synaptic depression (CER). In addition, we examined the functional consequences of variable DNA methylation within a PFC suicide-associated differentially methylated region (PSORS1C3 DMR) using a dual luciferase assay and examined expression of nearby genes. DNA methylation within this region was associated with decreased expression of firefly luciferase but was not associated with expression of nearby genes, PSORS1C3 and POU5F1. Our data suggest that suicide is associated with DNA methylation, offering novel insights into the molecular pathology associated with suicidality.Academy of Medical SciencesUK Medical Research CouncilNI

Profilin 1 negatively regulates osteoclast migration in postnatal skeletal growth, remodeling, and homeostasis in mice

Profilin 1 (Pfn1), a regulator of actin polymerization, controls cell movement in a context‐dependent manner. Pfn1 supports the locomotion of most adherent cells by assisting actin‐filament elongation, as has been shown in skeletal progenitor cells in our previous study. However, because Pfn1 has also been known to inhibit migration of certain cells, including T cells, by suppressing branched‐end elongation of actin filaments, we hypothesized that its roles in osteoclasts may be different from that of osteoblasts. By investigating the osteoclasts in culture, we first verified that Pfn1‐knockdown (KD) enhances bone resorption in preosteoclastic RAW264.7 cells, despite having a comparable number and size of osteoclasts. Pfn1‐KD in bone marrow cells showed similar results. Mechanistically, Pfn1‐KD osteoclasts appeared more mobile than in controls. In vivo, the osteoclast‐specific conditional Pfn1‐deficient mice (Pfn1‐cKO) by CathepsinK‐Cre driver demonstrated postnatal skeletal phenotype, including dwarfism, craniofacial deformities, and long‐bone metaphyseal osteolytic expansion, by 8 weeks of age. Metaphyseal and diaphyseal femurs were drastically expanded with suppressed trabecular bone mass as indicated by μCT analysis. Histologically, TRAP‐positive osteoclasts were increased at endosteal metaphysis to diaphysis of Pfn1‐cKO mice. The enhanced movement of Pfn1‐cKO osteoclasts in culture was associated with a slight increase in cell size and podosome belt length, as well as an increase in bone‐resorbing activity. Our study, for the first time, demonstrated that Pfn1 has critical roles in inhibiting osteoclast motility and bone resorption, thereby contributing to essential roles in postnatal skeletal homeostasis. Our study also provides novel insight into understanding skeletal deformities in human disorders