Involvement of extracellular vesicle microRNA clusters in developing healthy and Rett syndrome brain organoids.

Rett syndrome (RTT) is a neurodevelopmental disorder caused by de novo mutations in the MECP2 gene. Although miRNAs in extracellular vesicles (EVs) have been suggested to play an essential role in several neurological conditions, no prior study has utilized brain organoids to profile EV-derived miRNAs during normal and RTT-affected neuronal development. Here we report the spatiotemporal expression pattern of EV-derived miRNAs in region-specific forebrain organoids generated from female hiPSCs with a MeCP2:R255X mutation and the corresponding isogenic control. EV miRNA and protein expression profiles were characterized at day 0, day 13, day 40, and day 75. Several members of the hsa-miR-302/367 cluster were identified as having a time-dependent expression profile with RTT-specific alterations at the latest developmental stage. Moreover, the miRNA species of the chromosome 14 miRNA cluster (C14MC) exhibited strong upregulation in RTT forebrain organoids irrespective of their spatiotemporal location. Together, our results suggest essential roles of the C14MC and hsa-miR-302/367 clusters in EVs during normal and RTT-associated neurodevelopment, displaying promising prospects as biomarkers for monitoring RTT progression.

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.

Blood miR-144-3p: a novel diagnostic and therapeutic tool for depression.

Major depressive disorder (MDD) is the leading cause of disability worldwide. There is an urgent need for objective biomarkers to diagnose this highly heterogeneous syndrome, assign treatment, and evaluate treatment response and prognosis. MicroRNAs (miRNAs) are short non-coding RNAs, which are detected in body fluids that have emerged as potential biomarkers of many disease conditions. The present study explored the potential use of miRNAs as biomarkers for MDD and its treatment. We profiled the expression levels of circulating blood miRNAs from mice that were collected before and after exposure to chronic social defeat stress (CSDS), an extensively validated mouse model used to study depression, as well as after either repeated imipramine or single-dose ketamine treatment. We observed robust differences in blood miRNA signatures between stress-resilient and stress-susceptible mice after an incubation period, but not immediately after exposure to the stress. Furthermore, ketamine treatment was more effective than imipramine at re-establishing baseline miRNA expression levels, but only in mice that responded behaviorally to the drug. We identified the red blood cell-specific miR-144-3p as a candidate biomarker to aid depression diagnosis and predict ketamine treatment response in stress-susceptible mice and MDD patients. Lastly, we demonstrate that systemic knockdown of miR-144-3p, via subcutaneous administration of a specific antagomir, is sufficient to reduce the depression-related phenotype in stress-susceptible mice. RNA-sequencing analysis of blood after such miR-144-3p knockdown revealed a blunted transcriptional stress signature as well. These findings identify miR-144-3p as a novel target for diagnosis of MDD as well as for antidepressant treatment, and enhance our understanding of epigenetic processes associated with depression.

A systematically derived overview of the non-ubiquitous pathways and genes that define the molecular and genetic signature of the healthy trabecular meshwork.

PURPOSE: The trabecular meshwork (TM) is situated in the most frontal part of the eye and is thought to play an important role in the regulation of the eye pressure. However, this tissue is rather difficult to harvest for research. The purpose of this study is therefore to integrate the existing gene expression data of the healthy TM to increase sample size and identify its signature genes and pathways. This provides a robust reference for the study of molecular disease processes and supports the selection of candidate target genes for new treatments. METHODS: A systematic search identified microarray data of healthy TM tissue. After quality control, datasets of low quality and deviating samples were excluded. Remaining individuals were jointly normalized and integrated into one database. The average gene expression of each tested gene over all individuals was calculated. The 25% genes with the highest average expression were identified as the most active genes in the healthy TM and used as input for pathway and network analysis. Additionally, ubiquitous pathways and genes were identified and excluded from the results. Lastly, we identified genes which are likely to be TM-specific. RESULTS: The gene expression data of 44 individuals, obtained from 18 datasets, were jointly normalized. Ubiquitous genes (n = 688) and ubiquitous pathways (n = 73) were identified and excluded. Following, 1882 genes and 211 pathways were identified as the signature genes and pathways of the healthy TM. Pathway analysis revealed multiple molecular processes of which some were already known to be active in the TM, for example extracellular matrix and elastic fiber formation. Forty-six candidate TM-specific genes were identified. These consist mainly of pseudogenes or novel transcripts of which the function is unknown. CONCLUSIONS: In this comprehensive meta-analysis we identified non-ubiquitous genes and pathways that form the signature of the functioning of the healthy TM. Additionally, 46 candidate TM-specific genes were identified. This method can also be used for other tissues that are difficult to obtain for study.

To Predict, Prevent, and Manage Post-Traumatic Stress Disorder (PTSD): A Review of Pathophysiology, Treatment, and Biomarkers.

Post-traumatic stress disorder (PTSD) can become a chronic and severely disabling condition resulting in a reduced quality of life and increased economic burden. The disorder is directly related to exposure to a traumatic event, e.g., a real or threatened injury, death, or sexual assault. Extensive research has been done on the neurobiological alterations underlying the disorder and its related phenotypes, revealing brain circuit disruption, neurotransmitter dysregulation, and hypothalamic-pituitary-adrenal (HPA) axis dysfunction. Psychotherapy remains the first-line treatment option for PTSD given its good efficacy, although pharmacotherapy can also be used as a stand-alone or in combination with psychotherapy. In order to reduce the prevalence and burden of the disorder, multilevel models of prevention have been developed to detect the disorder as early as possible and to reduce morbidity in those with established diseases. Despite the clinical grounds of diagnosis, attention is increasing to the discovery of reliable biomarkers that can predict susceptibility, aid diagnosis, or monitor treatment. Several potential biomarkers have been linked with pathophysiological changes related to PTSD, encouraging further research to identify actionable targets. This review highlights the current literature regarding the pathophysiology, disease development models, treatment modalities, and preventive models from a public health perspective, and discusses the current state of biomarker research.

The Molecular Biology of Susceptibility to Post-Traumatic Stress Disorder: Highlights of Epigenetics and Epigenomics.

Exposure to trauma is one of the most important and prevalent risk factors for mental and physical ill-health. Excessive or prolonged stress exposure increases the risk of a wide variety of mental and physical symptoms. However, people differ strikingly in their susceptibility to develop signs and symptoms of mental illness after traumatic stress. Post-traumatic stress disorder (PTSD) is a debilitating disorder affecting approximately 8% of the world's population during their lifetime, and typically develops after exposure to a traumatic event. Despite that exposure to potentially traumatizing events occurs in a large proportion of the general population, about 80-90% of trauma-exposed individuals do not develop PTSD, suggesting an inter-individual difference in vulnerability to PTSD. While the biological mechanisms underlying this differential susceptibility are unknown, epigenetic changes have been proposed to underlie the relationship between exposure to traumatic stress and the susceptibility to develop PTSD. Epigenetic mechanisms refer to environmentally sensitive modifications to DNA and RNA molecules that regulate gene transcription without altering the genetic sequence itself. In this review, we provide an overview of various molecular biological, biochemical and physiological alterations in PTSD, focusing on changes at the genomic and epigenomic level. Finally, we will discuss how current knowledge may aid us in early detection and improved management of PTSD patients.

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.

WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities.

Visualizing the regulatory role of Angiopoietin-like protein 8 (ANGPTL8) in glucose and lipid metabolic pathways.

ANGPTL8 (Angiopoietin-like protein 8) is a newly identified hormone emerging as a novel drug target for treatment of diabetes mellitus and dyslipidemia due to its unique metabolic nature. With increasing number of studies targeting the regulation of ANGPTL8, integration of their findings becomes indispensable. This study has been conducted with the aim to collect, analyze, integrate and visualize the available knowledge in the literature about ANGPTL8 and its regulation. We utilized this knowledge to construct a regulatory pathway of ANGPTL8 which is available at WikiPathways, an open source pathways database. It allows us to visualize ANGPTL8's regulation with respect to other genes/proteins in different pathways helping us to understand the complex interplay of novel hormones/genes/proteins in metabolic disorders. To the best of our knowledge, this is the first attempt to present an integrated pathway view of ANGPTL8's regulation and its associated pathways and is important resource for future omics-based studies.

Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment.

BACKGROUND: Biological pathways are descriptive diagrams of biological processes widely used for functional analysis of differentially expressed genes or proteins. Primary data analysis, such as quality control, normalisation, and statistical analysis, is often performed in scripting languages like R, Perl, and Python. Subsequent pathway analysis is usually performed using dedicated external applications. Workflows involving manual use of multiple environments are time consuming and error prone. Therefore, tools are needed that enable pathway analysis directly within the same scripting languages used for primary data analyses. Existing tools have limited capability in terms of available pathway content, pathway editing and visualisation options, and export file formats. Consequently, making the full-fledged pathway analysis tool PathVisio available from various scripting languages will benefit researchers. RESULTS: We developed PathVisioRPC, an XMLRPC interface for the pathway analysis software PathVisio. PathVisioRPC enables creating and editing biological pathways, visualising data on pathways, performing pathway statistics, and exporting results in several image formats in multiple programming environments. We demonstrate PathVisioRPC functionalities using examples in Python. Subsequently, we analyse a publicly available NCBI GEO gene expression dataset studying tumour bearing mice treated with cyclophosphamide in R. The R scripts demonstrate how calls to existing R packages for data processing and calls to PathVisioRPC can directly work together. To further support R users, we have created RPathVisio simplifying the use of PathVisioRPC in this environment. We have also created a pathway module for the microarray data analysis portal ArrayAnalysis.org that calls the PathVisioRPC interface to perform pathway analysis. This module allows users to use PathVisio functionality online without having to download and install the software and exemplifies how the PathVisioRPC interface can be used by data analysis pipelines for functional analysis of processed genomics data. CONCLUSIONS: PathVisioRPC enables data visualisation and pathway analysis directly from within various analytical environments used for preliminary analyses. It supports the use of existing pathways from WikiPathways or pathways created using the RPC itself. It also enables automation of tasks performed using PathVisio, making it useful to PathVisio users performing repeated visualisation and analysis tasks. PathVisioRPC is freely available for academic and commercial use at http://projects.bigcat.unimaas.nl/pathvisiorpc.

A user-friendly workflow for analysis of Illumina gene expression bead array data available at the arrayanalysis.org portal.

BACKGROUND: Illumina whole-genome expression bead arrays are a widely used platform for transcriptomics. Most of the tools available for the analysis of the resulting data are not easily applicable by less experienced users. ArrayAnalysis.org provides researchers with an easy-to-use and comprehensive interface to the functionality of R and Bioconductor packages for microarray data analysis. As a modular open source project, it allows developers to contribute modules that provide support for additional types of data or extend workflows. RESULTS: To enable data analysis of Illumina bead arrays for a broad user community, we have developed a module for ArrayAnalysis.org that provides a free and user-friendly web interface for quality control and pre-processing for these arrays. This module can be used together with existing modules for statistical and pathway analysis to provide a full workflow for Illumina gene expression data analysis. The module accepts data exported from Illumina's GenomeStudio, and provides the user with quality control plots and normalized data. The outputs are directly linked to the existing statistics module of ArrayAnalysis.org, but can also be downloaded for further downstream analysis in third-party tools. CONCLUSIONS: The Illumina bead arrays analysis module is available at http://www.arrayanalysis.org . A user guide, a tutorial demonstrating the analysis of an example dataset, and R scripts are available. The module can be used as a starting point for statistical evaluation and pathway analysis provided on the website or to generate processed input data for a broad range of applications in life sciences research.

Differences in gene expression profiles between human preimplantation embryos cultured in two different IVF culture media.

STUDY QUESTION: Is gene expression in human preimplantation embryos affected by the medium used for embryo culture in vitro during an IVF treatment? SUMMARY ANSWER: Six days of in vitro culture of human preimplantation embryos resulted in medium-dependent differences in expression level of genes involved in apoptosis, protein degradation, metabolism and cell-cycle regulation. WHAT IS KNOWN ALREADY: Several human studies have shown an effect of culture medium on embryo development, pregnancy outcome and birthweight. However, the underlying mechanisms in human embryos are still unknown. In animal models of human development, it has been demonstrated that culture of preimplantation embryos in vitro affects gene expression. In humans, it has been found that culture medium affects gene expression of cryopreserved embryos that, after thawing, were cultured in two different media for 2 more days. STUDY DESIGN, SIZE, DURATION: In a multicenter trial, women were randomly assigned to two culture medium groups [G5 and human tubal fluid (HTF)]. Data on embryonic development were collected for all embryos. In one center, embryos originating from two pronuclei (2PN) zygotes that were not selected for transfer or cryopreservation on Day 2 or 3 because of lower morphological quality, were cultured until Day 6 and used in this study, if couples consented. PARTICIPANTS/MATERIALS, SETTING, METHODS: Ten blastocysts each from the G5 and HTF study groups, matched for fertilization method, maternal age and blastocyst quality, were selected and their mRNA was isolated and amplified. Embryos were examined individually for genome-wide gene expression using Agilent microarrays and PathVisio was used to identify the pathways that showed a culture medium-dependent activity. MAIN RESULTS AND THE ROLE OF CHANCE: Expression of 951 genes differed significantly (P < 0.01) between the G5 and HTF groups. Eighteen pathways, involved in apoptosis, metabolism, protein processing and cell-cycle regulation, showed a significant overrepresentation of differentially expressed genes. The DNA replication, G1 to S cell-cycle control and oxidative phosphorylation pathways were up-regulated in the G5 group compared with the HTF group. This is in agreement with the morphological assessment of the 1527 embryos (originating from 2PN zygotes), which showed that embryos consisted of more cells on Day 2 (3.73 ± 1.30 versus 3.40 ± 1.35, P < 0.001) and Day 3 (7.00 ± 2.41 versus 5.84 ± 2.36, P < 0.001) in the G5 group when compared with the HTF group. Furthermore, the implantation rate was significantly higher in the G5 group compared with the HTF group (26.7% versus 14.7%, P = 0.002) after transfer on the second or the third day after fertilization. LIMITATIONS, REASONS FOR CAUTION: Despite careful matching of the embryos, it cannot be excluded that the differences observed between the study groups are caused by factors that we did not investigate. Extrapolation of these results to embryos used for transfer demands caution as in the present study embryos that were not selected for either embryo transfer or cryopreservation have been used for the culture experiment until Day 6. WIDER IMPLICATIONS OF THE FINDINGS: This study shows that gene expression in human preimplantation embryos is altered by the culture medium used during IVF treatment and provides insight into the biological pathways that are affected. Whether these changes in gene expression have any long-term effects on children born after IVF remains unknown. However, it is possible that early adaptations of the preimplantation embryo to its environment persist during fetal and post-natal development. STUDY FUNDING/COMPETING INTERESTS: No funding and no competing interests declared. TRIAL REGISTRATION NUMBER: Not applicable.

User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org.

Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards.

Altered gene expression in human placentas after IVF/ICSI.

STUDY QUESTION: Is gene expression in placental tissue of IVF/ICSI patients altered when compared with a spontaneously conceived group, and are these alterations due to loss of imprinting (LOI) in the case of imprinted genes? SUMMARY ANSWER: An altered imprinted gene expression of H19 and Pleckstrin homology-like domain family A member 2 (PHLDA2), which was not due to LOI, was observed in human placentas after IVF/ICSI and several biological pathways were significantly overrepresented and mostly up-regulated. WHAT IS KNOWN ALREADY: Genomic imprinting plays an important role in placental biology and in placental adaptive responses triggered by external stimuli. Changes in placental development and function can have dramatic effects on the fetus and its ability to cope with the intrauterine environment. An increased frequency of placenta-related problems as well as an adverse perinatal outcome is seen in IVF/ICSI derived pregnancies, but the role of placental epigenetic deregulation is not clear yet. STUDY DESIGN AND PARTICIPANTS: In this prospective cohort study, a total of 115 IVF/ICSI and 138 control couples were included during pregnancy. After applying several exclusion criteria (i.e. preterm birth or stillbirth, no placental samples, pregnancy complications or birth defects), respectively, 81 and 105 placentas from IVF/ICSI and control pregnancies remained for analysis. Saliva samples were collected from both parents. METHODS: We quantitatively analysed the mRNA expression of several growth-related imprinted genes [H19, insulin-like growth factor 2 (IGF2), PHLDA2, cyclin-dependent kinase inhibitor 1C (CDKN1C), mesoderm-specific transcript homolog (MEST) isoform α and ß by quantitative PCR] after standardization against three housekeeping genes [Succinate dehydrogenase A (SDHA), YWHAZ and TATA-binding protein (TBP)]. A quantitative allele-specific expression analysis of the differentially expressed imprinted genes was performed to investigate LOI, independent of the mechanism of imprinting. Furthermore, a microarray analysis was carried out (n = 10 in each group) to investigate the expression of non-imprinted genes as well. MAIN RESULTS AND THE ROLE OF CHANCE: Both H19 and PHLDA2 showed a significant change, respectively, a 1.3-fold (P = 0.033) and 1.5-fold (P = 0.002) increase in mRNA expression in the IVF/ICSI versus control group. However, we found no indication that there is an increased frequency of LOI in IVF/ICSI placental samples. Genome-wide mRNA expression revealed 13 significantly overrepresented biological pathways involved in metabolism, immune response, transmembrane signalling and cell cycle control, which were mostly up-regulated in the IVF/ICSI placental samples. LIMITATIONS, REASONS FOR CAUTION: Only a subset of samples was found to be fully informative, which unavoidably led to lower sample numbers for our LOI analysis. Our study cannot distinguish whether the reported differences in the IVF/ICSI group are exclusively attributable to the IVF/ICSI technique itself or to the underlying subfertility of the patients. WIDER IMPLICATIONS OF THE FINDINGS: Whether these placental adaptations observed in pregnancies conceived by IVF/ICSI might be connected to an adverse perinatal outcome after IVF remains unknown. However, it is possible that these differences affect fetal development and long-term patterns of gene expression, as well as maternal gestational physiology. STUDY FUNDING/COMPETING INTERESTS: Partly funded by an unrestricted research grant by Organon BV (now MSD BV) and GROW School for Oncology and Developmental Biology without any role in study design, data collection and analysis or preparation of the manuscript. No conflict of interests to declare. TRIAL REGISTRATION NUMBER: Dutch Trial Registry (NTR) number 1298.

A novel insight into neurological disorders through HDAC6 protein-protein interactions.

Due to its involvement in physiological and pathological processes, histone deacetylase 6 (HDAC6) is considered a promising pharmaceutical target for several neurological manifestations. However, the exact regulatory role of HDAC6 in the central nervous system (CNS) is still not fully understood. Hence, using a semi-automated literature screening technique, we systematically collected HDAC6-protein interactions that are experimentally validated and reported in the CNS. The resulting HDAC6 network encompassed 115 HDAC6-protein interactions divided over five subnetworks: (de)acetylation, phosphorylation, protein complexes, regulatory, and aggresome-autophagy subnetworks. In addition, 132 indirect interactions identified through HDAC6 inhibition were collected and categorized. Finally, to display the application of our HDAC6 network, we mapped transcriptomics data of Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis on the network and highlighted that in the case of Alzheimer's disease, alterations predominantly affect the HDAC6 phosphorylation subnetwork, whereas differential expression within the deacetylation subnetwork is observed across all three neurological disorders. In conclusion, the HDAC6 network created in the present study is a novel and valuable resource for the understanding of the HDAC6 regulatory mechanisms, thereby providing a framework for the integration and interpretation of omics data from neurological disorders and pharmacodynamic assessments.

Dose-response relationship of MSCs as living Bio-drugs in HFrEF patients: a systematic review and meta-analysis of RCTs.

BACKGROUND: Mesenchymal stem cells (MSCs) have emerged as living biodrugs for myocardial repair and regeneration. Recent randomized controlled trials (RCTs) have reported that MSC-based therapy is safe and effective in heart failure patients; however, its dose-response relationship has yet to be established. We aimed to determine the optimal MSC dose for treating HF patients with reduced ejection fraction (EF) (HFrEF). METHODS: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) and Cochrane Handbook guidelines were followed. Four databases and registries, i.e., PubMed, EBSCO, clinicaltrials.gov, ICTRP, and other websites, were searched for RCTs. Eleven RCTs with 1098 participants (treatment group, n = 606; control group, n = 492) were selected based on our inclusion/exclusion criteria. Two independent assessors extracted the data and performed quality assessments. The data from all eligible studies were plotted for death, major adverse cardiac events (MACE), left ventricular ejection fraction (LVEF), left ventricular end-systolic volume (LVESV), and 6-minute walk distance (6-MWD) as safety, efficacy, and performance parameters. For dose-escalation assessment, studies were categorized as low-dose (< 100 million cells) or high-dose (≥ 100 million cells). RESULTS: MSC-based treatment is safe across low and high doses, with nonsignificant effects. However, low-dose treatment had a more significant protective effect than high-dose treatment. Subgroup analysis revealed the superiority of low-dose treatment in improving LVEF by 3.01% (95% CI; 0.65-5.38%) compared with high-dose treatment (-0.48%; 95% CI; -2.14-1.18). MSC treatment significantly improved the 6-MWD by 26.74 m (95% CI; 3.74-49.74 m) in the low-dose treatment group and by 36.73 m (95% CI; 6.74-66.72 m) in the high-dose treatment group. The exclusion of studies using ADRCs resulted in better safety and a significant improvement in LVEF from low- and high-dose MSC treatment. CONCLUSION: Low-dose MSC treatment was safe and superior to high-dose treatment in restoring efficacy and functional outcomes in heart failure patients, and further analysis in a larger patient group is warranted.

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies.

BACKGROUND: The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. RESULTS: We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. CONCLUSION: T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially.

A Public Health Perspective of Post-Traumatic Stress Disorder.

Trauma exposure is one of the most important and prevalent risk factors for mental and physical ill-health. Prolonged or excessive stress exposure increases the risk of a wide variety of mental and physical symptoms, resulting in a condition known as post-traumatic stress disorder (PTSD). The diagnosis might be challenging due to the complex pathophysiology and co-existence with other mental disorders. The prime factor for PTSD development is exposure to a stressor, which variably, along with peritraumatic conditions, affects disease progression and severity. Additionally, many factors are thought to influence the response to the stressor, and hence reshape the natural history and course of the disease. With sufficient knowledge about the disease, preventive and intervenient methods can be implemented to improve the quality of life of the patients and to limit both the medical and economic burden of the disease. This literature review provides a highlight of up-to-date literature on traumatic stress, with a focus on causes or triggers of stress, factors that influence response to stress, disease burden, and the application of the social-ecological public health model of disease prevention. In addition, it addresses therapeutic aspects, ethnic differences in traumatic stress, and future perspectives, including potential biomarkers.

Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease.

Cognitive impairment is a debilitating symptom in Parkinson's disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson's Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.

Sex-Specific Role for SLIT1 in Regulating Stress Susceptibility.

BACKGROUND: Major depressive disorder is a pervasive and debilitating syndrome characterized by mood disturbances, anhedonia, and alterations in cognition. While the prevalence of major depressive disorder is twice as high for women as men, little is known about the molecular mechanisms that drive sex differences in depression susceptibility. METHODS: We discovered that SLIT1, a secreted protein essential for axonal navigation and molecular guidance during development, is downregulated in the adult ventromedial prefrontal cortex (vmPFC) of women with depression compared with healthy control subjects, but not in men with depression. This sex-specific downregulation of Slit1 was also observed in the vmPFC of mice exposed to chronic variable stress. To identify a causal, sex-specific role for SLIT1 in depression-related behavioral abnormalities, we performed knockdown (KD) of Slit1 expression in the vmPFC of male and female mice. RESULTS: When combined with stress exposure, vmPFC Slit1 KD reflected the human condition by inducing a sex-specific increase in anxiety- and depression-related behaviors. Furthermore, we found that vmPFC Slit1 KD decreased the dendritic arborization of vmPFC pyramidal neurons and decreased the excitability of the neurons in female mice, effects not observed in males. RNA sequencing analysis of the vmPFC after Slit1 KD in female mice revealed an augmented transcriptional stress signature. CONCLUSIONS: Together, our findings establish a crucial role for SLIT1 in regulating neurophysiological and transcriptional responses to stress within the female vmPFC and provide mechanistic insight into novel signaling pathways and molecular factors influencing sex differences in depression susceptibility.

Altered sphingolipid function in Alzheimer's disease; a gene regulatory network approach.

Sphingolipids (SLs) are bioactive lipids involved in various important physiological functions. The SL pathway has been shown to be affected in several brain-related disorders, including Alzheimer's disease (AD). Recent evidence suggests that epigenetic dysregulation plays an important role in the pathogenesis of AD as well. Here, we use an integrative approach to better understand the relationship between epigenetic and transcriptomic processes in regulating SL function in the middle temporal gyrus of AD patients. Transcriptomic analysis of 252 SL-related genes, selected based on GO term annotations, from 46 AD patients and 32 healthy age-matched controls, revealed 103 differentially expressed SL-related genes in AD patients. Additionally, methylomic analysis of the same subjects revealed parallel hydroxymethylation changes in PTGIS, GBA, and ITGB2 in AD. Subsequent gene regulatory network-based analysis identified 3 candidate genes, that is, SELPLG, SPHK1 and CAV1 whose alteration holds the potential to revert the gene expression program from a diseased towards a healthy state. Together, this epigenomic and transcriptomic approach highlights the importance of SL-related genes in AD, and may provide novel biomarkers and therapeutic alternatives to traditionally investigated biological pathways in AD.