Identifying psychiatric and neurological comorbidities associated with hoarding disorder through network analysis.

BACKGROUND: The relationships between hoarding disorder (HD) and other neurological and psychiatric disorders remain largely unknown. Although psychiatric burden in those with HD is high, less is known about neurological disorders. Furthermore, which disorders are primarily associated with HD vs which can be better explained via a relationship with another disorder has not been determined. To address these questions, we examined comorbidity patterns of psychiatric and neurological disorders in a large online registry of adults using network analyses. METHODS: We first examined psychiatric comorbidity among 252 participants completing clinician administered psychiatric assessments. Using the Brain Health Registry (BHR) (N = 15,978), we next analyzed prevalence of self-reported neurological and psychiatric disorders among participants with no/minimal hoarding, subclinical hoarding, and clinically significant hoarding and used network analyses to identify direct and indirect relationships between HD and the assessed psychiatric and neurological disorders. RESULTS: The most prevalent comorbidity in clinically assessed participants with HD was major depressive disorder (MDD, 62%), followed by generalized anxiety disorder (GAD, 32%). Network analyses in the BHR indicated that the strongest direct relationships with HD were attention-deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and obsessive-compulsive disorder (OCD). The relationships between HD and neurological disorders, including mild cognitive impairment, were weak or non-existent after controlling for other disorders. CONCLUSIONS: ADHD, MDD, and OCD form a triad of psychiatric disorders directly associated with HD. Despite their high comorbidity rates, the associations among anxiety disorders and HD were weak or indirect.

Impact of Hoarding and Obsessive-Compulsive Disorder Symptomatology on Quality of Life and Their Interaction With Depression Symptomatology.

Hoarding disorder (HD) is a psychiatric condition characterized by difficulty discarding items and accumulation of clutter. Although studies have established the negative impact of HD and compulsive hoarding behavior, fewer have examined the impact on quality of life (QoL) of hoarding behavior independent of obsessive-compulsive disorder (OCD). Moreover, specific aspects of QoL such as success in work/academics or satisfaction with interpersonal relationships have not been well-investigated. In this study, we examined, in a sample of 2100 adult participants obtained from Amazon Mechanical Turk, the relationships between hoarding, OCD, and depression symptomatology and four QoL domains (success, enrichment, environment, and family) derived from a factor analysis of the Quality of Life Inventory (QoLI). We performed linear regressions to examine associations between psychiatric symptomatology and QoL domains and then conducted mediation analyses to investigate the role of depressive symptomatology in the identified relationships. We found that while hoarding and obsessive-compulsive symptoms were both negatively associated with QoL, they were associated with different domains [hoarding was significantly associated (p < 0.05) with total QoL and all domains and uniquely associated with environment and family QoL compared to obsessive-compulsive symptoms], whereas obsessive-compulsive symptoms were only significantly associated with total, success, and enrichment QoL. However, when depressive symptoms were included in the model, hoarding no longer accounted for significant variance in the total, environment, or family QoL domains (p > 0.05), and was less strongly associated with success or enrichment. Mediation analyses confirmed the role of depression as a complete mediator of hoarding's effect on total, environment, and family QoL, and as a partial mediator of hoarding's effect on success and enrichment QoL. Further examination of the relationship between hoarding symptoms and QoL in those with mild, moderate, and severe depression indicated that in those with more severe depression, hoarding was associated with improved QoL, indicating a possible buffering or compensatory effect. The findings suggest a differential impact of hoarding and obsessive-compulsive symptoms on QoL and emphasize the importance of considering co-morbid depressive symptoms in designing more targeted interventions. Future studies should continue to investigate these complex relationships, given the high co-morbidity of hoarding and depression.

Computational Modeling of Macrophage Iron Sequestration during Host Defense against Aspergillus.

Iron is essential to the virulence of Aspergillus species, and restricting iron availability is a critical mechanism of antimicrobial host defense. Macrophages recruited to the site of infection are at the crux of this process, employing multiple intersecting mechanisms to orchestrate iron sequestration from pathogens. To gain an integrated understanding of how this is achieved in aspergillosis, we generated a transcriptomic time series of the response of human monocyte-derived macrophages to Aspergillus and used this and the available literature to construct a mechanistic computational model of iron handling of macrophages during this infection. We found an overwhelming macrophage response beginning 2 to 4 h after exposure to the fungus, which included upregulated transcription of iron import proteins transferrin receptor-1, divalent metal transporter-1, and ZIP family transporters, and downregulated transcription of the iron exporter ferroportin. The computational model, based on a discrete dynamical systems framework, consisted of 21 3-state nodes, and was validated with additional experimental data that were not used in model generation. The model accurately captures the steady state and the trajectories of most of the quantitatively measured nodes. In the experimental data, we surprisingly found that transferrin receptor-1 upregulation preceded the induction of inflammatory cytokines, a feature that deviated from model predictions. Model simulations suggested that direct induction of transferrin receptor-1 (TfR1) after fungal recognition, independent of the iron regulatory protein-labile iron pool (IRP-LIP) system, explains this finding. We anticipate that this model will contribute to a quantitative understanding of iron regulation as a fundamental host defense mechanism during aspergillosis. IMPORTANCE Invasive pulmonary aspergillosis is a major cause of death among immunosuppressed individuals despite the best available therapy. Depriving the pathogen of iron is an essential component of host defense in this infection, but the mechanisms by which the host achieves this are complex. To understand how recruited macrophages mediate iron deprivation during the infection, we developed and validated a mechanistic computational model that integrates the available information in the field. The insights provided by this approach can help in designing iron modulation therapies as anti-fungal treatments.

Self-reporting of psychiatric illness in an online patient registry is a good indicator of the existence of psychiatric illness.

Online registries offer many advantages for research, including the ability to efficiently assess large numbers of individuals and identify potential participants for clinical trials and genetic studies. Of particular interest is the validity and utility of self-endorsement of psychiatric disorders in online registries, which, while increasingly more common, remain understudied. We thus assessed the comparability of prevalence estimated from self-endorsement of psychiatric disorders in one such registry, the Brain Health Registry (BHR) to prevalence computed from large US-based epidemiological studies and the degree to which BHR participants report psychiatric disorders consistently. We also examined the concordance between self-report and clinically determined diagnoses of various DSM-5 psychiatric disorders in a subset of participants who underwent direct assessments and identified possible reasons for discordance. Rates of self-reported psychiatric disorders were closest to previously reported population prevalence rates when endorsed at multiple timepoints, and accuracy was at least 70% for all except Hoarding Disorder as compared to the clinical diagnoses. Clinical data suggested that self-endorsement of a given psychiatric diagnosis was indicative of the presence of a closely related condition, although not necessarily for the specific disorder, with the exception of major depressive disorder, panic disorder, and hoarding disorder, which had high positive predictive values (85%, 73%, 100%, respectively). We conclude that self-reporting of psychiatric conditions in an online setting is a fair indicator of psychopathology, but should be accompanied by more in-depth interviews if using data from a participant for a specific disorder.

Aspergillus Utilizes Extracellular Heme as an Iron Source During Invasive Pneumonia, Driving Infection Severity.

BACKGROUND: Depriving microbes of iron is critical to host defense. Hemeproteins, the largest source of iron within vertebrates, are abundant in infected tissues in aspergillosis due to hemorrhage, but Aspergillus species have been thought to lack heme import mechanisms. We hypothesized that heme provides iron to Aspergillus during invasive pneumonia, thereby worsening the outcomes of the infection. METHODS: We assessed the effect of heme on fungal phenotype in various in vitro conditions and in a neutropenic mouse model of invasive pulmonary aspergillosis. RESULTS: In mice with neutropenic invasive aspergillosis, we found a progressive and compartmentalized increase in lung heme iron. Fungal cells cultured under low iron conditions took up heme, resulting in increased fungal iron content, resolution of iron starvation, increased conidiation, and enhanced resistance to oxidative stress. Intrapulmonary administration of heme to mice with neutropenic invasive aspergillosis resulted in markedly increased lung fungal burden, lung injury, and mortality, whereas administration of heme analogs or heme with killed Aspergillus did not. Finally, infection caused by fungal germlings cultured in the presence of heme resulted in a more severe infection. CONCLUSIONS: Invasive aspergillosis induces local hemolysis in infected tissues, thereby supplying heme iron to the fungus, leading to lethal infection.

Computational models in systems biology: standards, dissemination, and best practices.

Mathematical and computational models are a key technology in systems biology. Progress in the field depends on the replicability and reproducibility of their properties and behavior. For this, an essential requirement is a set of clear standards for model specification and dissemination. This review covers existing standards, and it highlights the most important areas where further work is required. This includes the specification of agent-based models, an increasingly common modeling approach.

SteadyCellPhenotype: a web-based tool for the modeling of biological networks with ternary logic.

SUMMARY: We introduce SteadyCellPhenotype, a browser-based interface for the analysis of ternary biological networks. It includes tools for deterministically finding all steady states of a network, as well as the simulation and visualization of trajectories with publication quality graphics. Simulations allow us to approximate the size of the basin for attractors and deterministic simulations of trajectories nearby specified points allow us to explore the behavior of the system in that neighborhood. AVAILABILITY AND IMPLEMENTATION: https://github.com/knappa/steadycellphenotype MIT License.

Control of Intracellular Molecular Networks Using Algebraic Methods.

Many problems in biology and medicine have a control component. Often, the goal might be to modify intracellular networks, such as gene regulatory networks or signaling networks, in order for cells to achieve a certain phenotype, what happens in cancer. If the network is represented by a mathematical model for which mathematical control approaches are available, such as systems of ordinary differential equations, then this problem might be solved systematically. Such approaches are available for some other model types, such as Boolean networks, where structure-based approaches have been developed, as well as stable motif techniques. However, increasingly many published discrete models are mixed-state or multistate, that is, some or all variables have more than two states, and thus the development of control strategies for multistate networks is needed. This paper presents a control approach broadly applicable to general multistate models based on encoding them as polynomial dynamical systems over a finite algebraic state set, and using computational algebra for finding appropriate intervention strategies. To demonstrate the feasibility and applicability of this method, we apply it to a recently developed multistate intracellular model of E2F-mediated bladder cancerous growth and to a model linking intracellular iron metabolism and oncogenic pathways. The control strategies identified for these published models are novel in some cases and represent new hypotheses, or are supported by the literature in others as potential drug targets. Our Macaulay2 scripts to find control strategies are publicly available through GitHub at https://github.com/luissv7/multistatepdscontrol.