Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention

Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases.

Inflammatory bowel diseases, which include Crohn's disease and ulcerative colitis, affect several million individuals worldwide. Crohn's disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Finally, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study's infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi'omics Database ( http://ibdmdb.org ), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases

An integrative analysis of cancer gene expression studies using Bayesian latent factor modeling

We present an applied study in cancer genomics for integrating data and inferences from laboratory experiments on cancer cell lines with observational data obtained from human breast cancer studies. The biological focus is on improving understanding of transcriptional responses of tumors to changes in the pH level of the cellular microenvironment. The statistical focus is on connecting experimentally defined biomarkers of such responses to clinical outcome in observational studies of breast cancer patients. Our analysis exemplifies a general strategy for accomplishing this kind of integration across contexts. The statistical methodologies employed here draw heavily on Bayesian sparse factor models for identifying, modularizing and correlating with clinical outcome these signatures of aggregate changes in gene expression. By projecting patterns of biological response linked to specific experimental interventions into observational studies where such responses may be evidenced via variation in gene expression across samples, we are able to define biomarkers of clinically relevant physiological states and outcomes that are rooted in the biology of the original experiment. Through this approach we identify microenvironment-related prognostic factors capable of predicting long term survival in two independent breast cancer datasets. These results suggest possible directions for future laboratory studies, as well as indicate the potential for therapeutic advances though targeted disruption of specific pathway components.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS261 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Identification of molecular markers of delayed graft function based on the regulation of biological ageing

Introduction: Delayed graft function is a prevalent clinical problem in renal transplantation for which there is no objective system to predict occurrence in advance. It can result in a significant increase in the necessity for hospitalisation post-transplant and is a significant risk factor for other post-transplant complications. Methodology: The importance of microRNAs (miRNAs), a specific subclass of small RNA, have been clearly demonstrated to influence many pathways in health and disease. To investigate the influence of miRNAs on renal allograft performance post-transplant, the expression of a panel of miRNAs in pre-transplant renal biopsies was measured using qPCR. Expression was then related to clinical parameters and outcomes in two independent renal transplant cohorts. Results: Here we demonstrate, in two independent cohorts of pre-implantation human renal allograft biopsies, that a novel pre-transplant renal performance scoring system (GRPSS), can determine the occurrence of DGF with a high sensitivity (>90%) and specificity (>60%) for donor allografts pre-transplant, using just three senescence associated microRNAs combined with donor age and type of organ donation. Conclusion: These results demonstrate a relationship between pre-transplant microRNA expression levels, cellular biological ageing pathways and clinical outcomes for renal transplantation. They provide for a simple, rapid quantitative molecular pre-transplant assay to determine post-transplant allograft function and scope for future intervention. Furthermore, these results demonstrate the involvement of senescence pathways in ischaemic injury during the organ transplantation process and an indication of accelerated bio-ageing as a consequence of both warm and cold ischaemia

Functional Effects of let-7g Expression in Colon Cancer Metastasis.

MicroRNA regulation is crucial for gene expression and cell functions. It has been linked to tumorigenesis, development and metastasis in colorectal cancer (CRC). Recently, the let-7 family has been identified as a tumor suppressor in different types of cancers. However, the function of the let-7 family in CRC metastasis has not been fully investigated. Here, we focused on analyzing the role of let-7g in CRC. The Cancer Genome Atlas (TCGA) genomic datasets of CRC and detailed data from a Taiwanese CRC cohort were applied to study the expression pattern of let-7g. In addition, in vitro as well as in vivo studies have been performed to uncover the effects of let-7g on CRC. We found that the expression of let-7g was significantly lower in CRC specimens. Our results further supported the inhibitory effects of let-7g on CRC cell migration, invasion and extracellular calcium influx through store-operated calcium channels. We report a critical role for let-7g in the pathogenesis of CRC and suggest let-7g as a potential therapeutic target for CRC treatment

Gut Microbial Metabolism and Nonalcoholic Fatty Liver Disease.

The gut microbiome, the multispecies community of microbes that exists in the gastrointestinal tract, encodes several orders of magnitude more functional genes than the human genome. It also plays a pivotal role in human health, in part due to metabolism of environmental, dietary, and host-derived substrates, which produce bioactive metabolites. Perturbations to the composition and associated metabolic output of the gut microbiome have been associated with a number of chronic liver diseases, including nonalcoholic fatty liver disease (NAFLD). Here, we review the rapidly evolving suite of next-generation techniques used for studying gut microbiome composition, functional gene content, and bioactive products and discuss relationships with the pathogenesis of NAFLD

DNA methylation analysis of the angiotensin converting enzyme (ACE) gene in major depression.

The angiotensin converting enzyme (ACE) has been repeatedly discussed as susceptibility factor for major depression (MD) and the bi-directional relation between MD and cardiovascular disorders (CVD). In this context, functional polymorphisms of the ACE gene have been linked to depression, to antidepressant treatment response, to ACE serum concentrations, as well as to hypertension, myocardial infarction and CVD risk markers. The mostly investigated ACE Ins/Del polymorphism accounts for ~40%-50% of the ACE serum concentration variance, the remaining half is probably determined by other genetic, environmental or epigenetic factors, but these are poorly understood. The main aim of the present study was the analysis of the DNA methylation pattern in the regulatory region of the ACE gene in peripheral leukocytes of 81 MD patients and 81 healthy controls. We detected intensive DNA methylation within a recently described, functional important region of the ACE gene promoter including hypermethylation in depressed patients (p = 0.008) and a significant inverse correlation between the ACE serum concentration and ACE promoter methylation frequency in the total sample (p = 0.02). Furthermore, a significant inverse correlation between the concentrations of the inflammatory CVD risk markers ICAM-1, E-selectin and P-selectin and the degree of ACE promoter methylation in MD patients could be demonstrated (p = 0.01 - 0.04). The results of the present study suggest that aberrations in ACE promoter DNA methylation may be an underlying cause of MD and probably a common pathogenic factor for the bi-directional relationship between MD and cardiovascular disorders