GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function

Abstract Background: Most successful computational approaches for protein function prediction integrate multiple genomics and proteomics data sources to make inferences about the function of unknown proteins. The most accurate of these algorithms have long running times, making them unsuitable for real-time protein function prediction in large genomes. As a result, the predictions of these algorithms are stored in static databases that can easily become outdated. We propose a new algorithm, GeneMANIA, that is as accurate as the leading methods, while capable of predicting protein function in real-time. Results: We use a fast heuristic algorithm, derived from ridge regression, to integrate multiple functional association networks and predict gene function from a single process-specific network using label propagation. Our algorithm is efficient enough to be deployed on a modern webserver and is as accurate as, or more so than, the leading methods on the MouseFunc I benchmark and a new yeast function prediction benchmark; it is robust to redundant and irrelevant data and requires, on average, less than ten seconds of computation time on tasks from these benchmarks. Conclusion: GeneMANIA is fast enough to predict gene function on-the-fly while achieving state-of-the-art accuracy. A prototype version of a GeneMANIA-based webserver is available at http://morrislab.med.utoronto.ca/prototype

Designing Virtual Environments for Social Engagement in Older Adults

Virtual reality (VR) is increasingly used as a platform for social interaction, including as a means for older adults to maintain engagement. However, there has been limited research to examine the features of social VR that are most relevant to older adults experiences. The current study was conducted to qualitatively analyze the behavior of older adults in a collaborative VR environment and evaluate aspects of design that affected their engagement outcomes. We paired 36 participants over the age of 60, from three diverse geographic locations, and asked them to interact in collaborative VR modules. Video-based observation methods and thematic analyses were used to study the resulting interactions. The results indicated a strong link between perceived spatial presence in the VR and social engagement, while also highlighting the importance of individual personality and compatibility. The study provides new insights into design guidelines that could improve social VR programs for older adults

Inhalation of diesel exhaust and allergen alters human bronchial epithelium DNA methylation

Background Allergic disease affects 30% to 40% of the world's population, and its development is determined by the interplay between environmental and inherited factors. Air pollution, primarily consisting of diesel exhaust emissions, has increased at a similar rate to allergic disease. Exposure to diesel exhaust may play a role in the development and progression of allergic disease, in particular allergic respiratory disease. One potential mechanism underlying the connection between air pollution and increased allergic disease incidence is DNA methylation, an epigenetic process with the capacity to integrate gene-environment interactions. Objective We sought to investigate the effect of allergen and diesel exhaust exposure on bronchial epithelial DNA methylation. Methods We performed a randomized crossover-controlled exposure study to allergen and diesel exhaust in humans, and measured single-site (CpG) resolution global DNA methylation in bronchial epithelial cells. Results Exposure to allergen alone, diesel exhaust alone, or allergen and diesel exhaust together (coexposure) led to significant changes in 7 CpG sites at 48 hours. However, when the same lung was exposed to allergen and diesel exhaust but separated by approximately 4 weeks, significant changes in more than 500 sites were observed. Furthermore, sites of differential methylation differed depending on which exposure was experienced first. Functional analysis of differentially methylated CpG sites found genes involved in transcription factor activity, protein metabolism, cell adhesion, and vascular development, among others. Conclusions These findings suggest that specific exposures can prime the lung for changes in DNA methylation induced by a subsequent insult

The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function

GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist

Deconvolving the contributions of cell-type heterogeneity on cortical gene expression

Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer\u27s disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs)

The Impact of Adolescent Friendships on Unhealthy Eating Behaviors of Overweight and Obese Adolescents: A Qualitative Study

Background: Childhood obesity has reached epidemic proportions and become one the most important public health issues globally. One of the significant determinants of childhood obesity-related behaviors such as poor dietary habits relates to role of friends and peers. This study aimed toexplore the role of interaction within the social network of friends on unhealthy eating behaviors of overweight and obese adolescents. Materials and Methods: This qualitative study was conducted between 2016 and 2017 in Mashhad and Isfahan, two large cities of Iran. Ten parents and 52 overweight and obese adolescents were selected through purposeful sampling. To obtain perceptions and experiences regarding the role of adolescent friendships on unhealthy eating behaviors, in-depth semi-structured interviews and focus group discussions were conducted. Data were analyzed based on conventional content analysis. Results: Six themes which contributed to following unhealthy dietary habits when adolescents are in the friend networks were identified: "Eating in the peer networks as a usual way for social interaction", "Peers’ pressure to have unhealthy dietary habits", "High availability and accessibility to unhealthy foods", "Lack of nutritional knowledge", "Neglectful parenting style", and "Passive interaction in the friendship networks". Conclusion: Our findings indicate that peer support along with appropriate parenting style are necessary to affect adolescent eating behaviors when they are in the friend social networks, but are not sufficient per se. Being a confident, decisive and self-determined adolescent and owing a high level of behavioral confidence and self-esteem might reduce the impact of friends for adhering to unhealthy dietary habits in youth

Multi-omic Directed Networks Describe Features of Gene Regulation in Aged Brains and Expand the Set of Genes Driving Cognitive Decline

Multiple aspects of molecular regulation, including genetics, epigenetics, and mRNA collectively influence the development of age-related neurologic diseases. Therefore, with the ultimate goal of understanding molecular systems associated with cognitive decline, we infer directed interactions among regulatory elements in the local regulatory vicinity of individual genes based on brain multi-omics data from 413 individuals. These local regulatory networks (LRNs) capture the influences of genetics and epigenetics on gene expression in older adults. LRNs were confirmed through correspondence to known transcription biophysics. To relate LRNs to age-related neurologic diseases, we then incorporate common neuropathologies and measures of cognitive decline into this framework. This step identifies a specific set of largely neuronal genes, such as STAU1 and SEMA3F, predicted to control cognitive decline in older adults. These predictions are validated in separate cohorts by comparison to genetic associations for general cognition. LRNs are shared through www.molecular.network on the Rush Alzheimer’s Disease Center Resource Sharing Hub (www.radc.rush.edu)

Recurrent cannabis-induced catatonia: a case report and comprehensive systematic literature review

BackgroundCatatonia presents itself as a complex neuropsychiatric syndrome, giving rise to various motor, speech, and behavioral challenges. It is noteworthy that approximately 10% of psychiatric hospital admissions can be attributed to this condition. It is imperative to note that cannabis-induced catatonia, while infrequent, has been linked to the use of marijuana. This connection has the potential to disrupt neurotransmitter systems, necessitating further research for a comprehensive understanding and effective treatment, particularly given the evolving trends in cannabis use. In this context, we shall delve into a unique case of recurrent cannabis-induced catatonia.Case presentationA 23-year-old gentleman, who has previously struggled with substance use disorder, experienced the emergence of mutism, social isolation, and a fixed gaze subsequent to his use of cannabis. Remarkably, despite the absence of hallucinations, he exhibited recurrent episodes of catatonia. These episodes were effectively addressed through a combination of electroconvulsive therapy (ECT) and lorazepam administration. Notably, when the lorazepam dosage was gradually reduced to below 2 mg per day, the catatonic symptoms resurfaced; however, they promptly abated upon reinstating the medication. The diagnosis of cannabis-induced catatonia was established, and its management primarily involved a therapeutic approach encompassing ECT and lorazepam. It is pertinent to underscore that this catatonic condition can be directly linked to the individual’s cannabis usage.ConclusionThe connection between cannabis and catatonia is intricate and not entirely comprehended. Although cannabis possesses therapeutic advantages, it can paradoxically trigger catatonia in certain individuals. Multiple factors, such as genetics, cannabinoids, and neurotransmitter systems, contribute to this intricacy, underscoring the necessity for additional research

The Molecular and Neuropathological Consequences of Genetic Risk for Alzheimer's Dementia

Alzheimer's dementia commonly impacts the health of older adults and lacks any preventative therapy. While Alzheimer's dementia risk has a substantial genetic component, the specific molecular mechanisms and neuropathologies triggered by most of the known genetic variants are unclear. Resultantly, they have shown limited influence on drug development portfolios to date. To facilitate our understanding of the consequences of Alzheimer's dementia susceptibility variants, we examined their relationship to a wide range of clinical, molecular and neuropathological features. Because the effect size of individual variants is typically small, we utilized a polygenic (overall) risk approach to identify the global impact of Alzheimer's dementia susceptibility variants. Under this approach, each individual has a polygenic risk score (PRS) that we related to clinical, molecular and neuropathological phenotypes. Applying this approach to 1,272 individuals who came to autopsy from one of two longitudinal aging cohorts, we observed that an individual's PRS was associated with cognitive decline and brain pathologies including beta-amyloid, tau-tangles, hippocampal sclerosis, and TDP-43, MIR132, four proteins including VGF, IGFBP5, and STX1A, and many chromosomal regions decorated with acetylation on histone H3 lysine 9 (H3K9Ac). While excluding the APOE/TOMM40 region (containing the single largest genetic risk factor for late-onset Alzheimer's dementia) in the calculation of the PRS resulted in a slightly weaker association with the molecular signatures, results remained significant. These PRS-associated brain pathologies and molecular signatures appear to mediate genetic risk, as they attenuated the association of the PRS with cognitive decline. Notably, the PRS induced changes in H3K9Ac throughout the genome, implicating it in large-scale chromatin changes. Thus, the PRS for Alzheimer's dementia (AD-PRS) showed effects on diverse clinical, molecular, and pathological systems, ranging from the epigenome to specific proteins. These convergent targets of a large number of genetic risk factors for Alzheimer's dementia will help define the experimental systems and models needed to test therapeutic targets, which are expected to be broadly effective in the aging population that carries diverse genetic risks for Alzheimer's dementia