Course of avoidant/restrictive food intake disorder: Emergence of overvaluation of shape/weight.

BACKGROUND: Avoidant/restrictive food intake disorder (ARFID) is a feeding/eating disorder characterized by avoidance/restriction of food intake by volume and/or variety. The emergence of shape/weight-related eating disorder symptoms in the longitudinal course of ARFID is an important clinical phenomenon that is neither robustly documented nor well understood. We aimed to characterize the emergence of eating disorder symptoms among adults with an initial diagnosis of ARFID who ultimately developed other eating disorders. METHOD: Thirty-five participants (94% female; Mage = 23.17 ± 5.84 years) with a history of ARFID and a later, separate eating disorder completed clinical interviews (i.e., Structured Clinical Interview for DSM-5 - Research Version and Longitudinal Interval Follow-Up Evaluation) assessing the period between ARFID and the later eating disorder. Participants used calendars to aid in recall of symptoms over time. Descriptive statistics characterized the presence, order of, and time to each symptom. Paired samples t-tests compared weeks to emergence between symptoms. RESULTS: Most participants (71%) developed restricting eating disorders; the remainder (29%) developed binge-spectrum eating disorders. Cognitive symptoms (e.g., shape/weight concerns) tended to onset initially and were followed by behavioral symptoms. Shape/weight-related food avoidance presented first, objective binge eating, fasting, and excessive exercise occurred next, followed by subjective binge eating and purging. CONCLUSIONS: Diagnostic crossover from ARFID to another (typically restricting) eating disorder following the development of shape/weight concerns may represent the natural progression of a singular clinical phenomenon. Findings identify potential pathways from ARFID to the development of another eating disorder, highlighting possible clinical targets for preventing this outcome.

Intraspecies warfare restricts strain coexistence in human skin microbiomes.

Determining why only a fraction of encountered or applied bacterial strains engraft in a given person's microbiome is crucial for understanding and engineering these communities 1 . Previous work has established that metabolism can determine colonization success in vivo 2-4 , but relevance of bacterial warfare in preventing engraftment has been less explored. Here, we demonstrate that intraspecies warfare presents a significant barrier to strain transmission in the skin microbiome by profiling 14,884 pairwise interactions between Staphylococcus epidermidis cultured from eighteen human subjects from six families. We find that intraspecies antagonisms are abundant; these interactions are mechanistically diverse, independent of the relatedness between strains, and consistent with rapid evolution via horizontal gene transfer. Ability to antagonize more strains is associated with reaching a higher fraction of the on-person S. epidermidis community. Moreover, antagonisms are significantly depleted among strains residing on the same person relative to random assemblages. Two notable exceptions, in which bacteria evolved to become sensitive to antimicrobials found on the same host, are explained by mutations that provide phage resistance, contextualizing the importance of warfare among other lethal selective pressures. Taken together, our results emphasize that accounting for intraspecies bacterial warfare is essential to the design of long-lasting probiotic therapeutics.

Arginine-NO metabolites are associated with morbidity in single ventricle infants undergoing stage 2 palliation.

BACKGROUND: Infants with single ventricle heart disease (SVHD) suffer morbidity from insufficient pulmonary blood flow, which may be related to impaired arginine metabolism. No prior study has reported quantitative mapping of arginine metabolites to evaluate the relationship between circulating metabolite levels and outcomes. METHODS: Prospective cohort study of 75 SVHD cases peri-Stage 2 and 50 healthy controls. We targeted pre- and post-op absolute serum quantification of 9 key members of the arginine metabolism pathway by tandem mass spectrometry. Primary outcomes were length of stay (LOS) and post-Stage 2 hypoxemia. RESULTS: Pre-op cases showed alteration in 6 metabolites including decreased arginine and increased asymmetric dimethyl arginine (ADMA) levels compared to controls. Post-op cases demonstrated decreased arginine and citrulline levels persisting through 48 h. Adjusting for clinical variables, lower pre-op and 2 h post-op concentrations of multiple metabolites, including arginine and citrulline, were associated with longer post-op LOS (p < 0.01). Increased ADMA at 24 h was associated with greater post-op hypoxemia burden (p < 0.05). CONCLUSION: Arginine metabolism is impaired in interstage SVHD infants and is further deranged following Stage 2 palliation. Patients with greater metabolite alterations experience greater post-op morbidity. Decreased arginine metabolism may be an important driver of pathology in SVHD. IMPACT: Interstage infants with SVHD have significantly altered arginine-nitric oxide metabolism compared to healthy children with deficiency of multiple pathway intermediates persisting through 48 h post-Stage 2 palliation. After controlling for clinical covariates and classic catheterization-derived predictors of Stage 2 readiness, both lower pre-operation and lower post-operation circulating metabolite levels were associated with longer post-Stage 2 LOS while increased post-Stage 2 ADMA concentration was associated with greater post-op hypoxemia. Arginine metabolism mapping offers potential for development using personalized medicine strategies as a biomarker of Stage 2 readiness and therapeutic target to improve pulmonary vascular health in infants with SVHD.

Joint representation of molecular networks from multiple species improves gene classification.

Network-based machine learning (ML) has the potential for predicting novel genes associated with nearly any health and disease context. However, this approach often uses network information from only the single species under consideration even though networks for most species are noisy and incomplete. While some recent methods have begun addressing this shortcoming by using networks from more than one species, they lack one or more key desirable properties: handling networks from more than two species simultaneously, incorporating many-to-many orthology information, or generating a network representation that is reusable across different types of and newly-defined prediction tasks. Here, we present GenePlexusZoo, a framework that casts molecular networks from multiple species into a single reusable feature space for network-based ML. We demonstrate that this multi-species network representation improves both gene classification within a single species and knowledge-transfer across species, even in cases where the inter-species correspondence is undetectable based on shared orthologous genes. Thus, GenePlexusZoo enables effectively leveraging the high evolutionary molecular, functional, and phenotypic conservation across species to discover novel genes associated with diverse biological contexts.

Highly-resolved within-species dynamics in the human facial skin microbiome.

Human facial skin microbiomes (FSMs) on adults are dominated by just two bacterial species, Cutibacterium acnes and Staphylococcus epidermidis. Underlying this apparent simplicity, each FSM harbors multiple strains of both species whose assembly dynamics on individuals are unknown. Here, we use 4,055 isolate genomes and 360 metagenomes to trace the dynamics of strains on individuals and their transmission. Strains are shared amongst family members of all ages, but each individual harbors unique strain consortia. Strain stability changes upon formation of the adult-type FSM: S. epidermidis lineage turnover slows, and the rate of C. acnes colonization increases before stabilizing, suggesting this transitional window could facilitate engraftment of therapeutic strains. Our work reveals previously undetectable community dynamics and informs the design of therapeutic interventions.

The proteomic fingerprint in infants with single ventricle heart disease in the interstage period: evidence of chronic inflammation and widespread activation of biological networks.

Introduction: Children with single ventricle heart disease (SVHD) experience significant morbidity across systems and time, with 70% of patients experiencing acute kidney injury, 33% neurodevelopmental impairment, 14% growth failure, and 5.5% of patients suffering necrotizing enterocolitis. Proteomics is a method to identify new biomarkers and mechanisms of injury in complex physiologic states. Methods: Infants with SVHD in the interstage period were compared to similar-age healthy controls. Serum samples were collected, stored at -80°C, and run on a panel of 1,500 proteins in single batch analysis (Somalogic Inc., CO). Partial Least Squares-Discriminant Analysis (PLS-DA) was used to compare the proteomic profile of cases and controls and t-tests to detect differences in individual proteins (FDR <0.05). Protein network analysis with functional enrichment was performed in STRING and Cytoscape. Results: PLS-DA readily discriminated between SVHD cases (n = 33) and controls (n = 24) based on their proteomic pattern alone (Accuracy = 0.96, R2 = 0.97, Q2 = 0.80). 568 proteins differed between groups (FDR <0.05). We identified 25 up-regulated functional clusters and 13 down-regulated. Active biological systems fell into six key groups: angiogenesis and cell proliferation/turnover, immune system activation and inflammation, altered metabolism, neural development, gastrointestinal system, and cardiac physiology and development. Conclusions: We report a clear differentiation in the circulating proteome of patients with SVHD and healthy controls with >500 circulating proteins distinguishing the groups. These proteomic data identify widespread protein dysregulation across multiple biologic systems with promising biological plausibility as drivers of SVHD morbidity.

Engineering Escherichia coli for diagnosis and management of hyperuricemia.

Uric acid disequilibrium is implicated in chronic hyperuricemia-related diseases. Long-term monitoring and lowering of serum uric acid levels may be crucial for diagnosis and effective management of these conditions. However, current strategies are not sufficient for accurate diagnosis and successful long-term management of hyperuricemia. Moreover, drug-based therapeutics can cause side effects in patients. The intestinal tract plays an important role in maintaining healthy serum acid levels. Hence, we investigated the engineered human commensal Escherichia coli as a novel method for diagnosis and long-term management of hyperuricemia. To monitor changes in uric acid concentration in the intestinal lumen, we developed a bioreporter using the uric acid responsive synthetic promoter, pucpro, and uric acid binding Bacillus subtilis PucR protein. Results demonstrated that the bioreporter module in commensal E. coli can detect changes in uric acid concentration in a dose-dependent manner. To eliminate the excess uric acid, we designed a uric acid degradation module, which overexpresses an E. coli uric acid transporter and a B. subtilis urate oxidase. Strains engineered with this module degraded all the uric acid (250 µM) found in the environment within 24 h, which is significantly lower (p < 0.001) compared to wild type E. coli. Finally, we designed an in vitro model using human intestinal cell line, Caco-2, which provided a versatile tool to study the uric acid transport and degradation in an environment mimicking the human intestinal tract. Results showed that engineered commensal E. coli reduced (p < 0.01) the apical uric acid concentration by 40.35% compared to wild type E. coli. This study shows that reprogramming E. coli holds promise as a valid alternative synthetic biology therapy to monitor and maintain healthy serum uric acid levels.

Neural activation of regions involved in food reward and cognitive control in young females with anorexia nervosa and atypical anorexia nervosa versus healthy controls.

Anorexia nervosa (AN) and atypical AN (AtypAN) are complex neurobiological illnesses that typically onset in adolescence with an often treatment-refractory and chronic illness trajectory. Aberrant eating behaviors in this population have been linked to abnormalities in food reward and cognitive control, but prior studies have not examined respective contributions of clinical characteristics and metabolic state. Research is needed to identify specific disruptions and inform novel intervention targets to improve outcomes. Fifty-nine females with AN (n = 34) or AtypAN (n = 25), ages 10-22 years, all ≤90% expected body weight, and 34 age-matched healthy controls (HC) completed a well-established neuroimaging food cue paradigm fasting and after a standardized meal, and we used ANCOVA models to investigate main and interaction effects of Group and Appetitive State on blood oxygenation level-dependent (BOLD) activation for the contrast of exposure to high-calorie food images minus objects. We found main effects of Group with greater BOLD activation in the dorsal anterior cingulate cortex (dACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, caudate, and putamen for AN/AtypAN versus HC groups, and in the three-group model including AN, AtypAN, and HC (sub-)groups, where differences were primarily driven by greater activation in the AtypAN subgroup versus HC group. We found a main effect of Appetitive State with increased premeal BOLD activation in the hypothalamus, amygdala, nucleus accumbens, and caudate for models that included AN/AtypAN and HC groups, and in BOLD activation in the nucleus accumbens for the model that included AN, AtypAN, and HC (sub-)groups. There were no interaction effects of Group with Appetitive State for any of the models. Our findings demonstrate robust feeding-state independent group effects reflecting greater neural activation of specific regions typically associated with reward and cognitive control processing across AN and AtypAN relative to healthy individuals in this food cue paradigm. Differential activation of specific brain regions in response to the passive viewing of high-calorie food images may underlie restrictive eating behavior in this clinical population.

PyGenePlexus: a Python package for gene discovery using network-based machine learning.

SUMMARY: PyGenePlexus is a Python package that enables a user to gain insight into any gene set of interest through a molecular interaction network informed supervised machine learning model. PyGenePlexus provides predictions of how associated every gene in the network is to the input gene set, offers interpretability by comparing the model trained on the input gene set to models trained on thousands of known gene sets, and returns the network connectivity of the top predicted genes. AVAILABILITY AND IMPLEMENTATION: https://pypi.org/project/geneplexus/ and https://github.com/krishnanlab/PyGenePlexus. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Delusionality of beliefs among 50 adult females with severe and extreme anorexia nervosa upon admission to an acute medical stabilization facility.

We aimed to evaluate whether the content of eating/body image-related beliefs in individuals with anorexia nervosa (AN) was associated with important aspects of eating disorder (ED) psychopathology. Females with AN completed assessments within 96 hours of admission to an inpatient medical stabilization program. Study staff administered the Brown Assessment of Beliefs Scale and participants completed self-report measures. We derived belief content domains using an inductive approach and examined associations between beliefs and clinical variables. The following belief categories emerged (% with a belief in that category): body image beliefs (64%), food beliefs (30%), body function beliefs (20%), rejection of illness beliefs (12%), morality beliefs (10%), and control beliefs (6%). No one belief domain was significantly associated with greater delusional intensity. However, findings indicate that greater delusionality was generally associated with worse ED psychopathology.

Enhancing nutritional niche and host defenses by modifying the gut microbiome.

The gut microbiome is essential for processing complex food compounds and synthesizing nutrients that the host cannot digest or produce, respectively. New model systems are needed to study how the metabolic capacity provided by the gut microbiome impacts the nutritional status of the host, and to explore possibilities for altering host metabolic capacity via the microbiome. Here, we colonized the nematode Caenorhabditis elegans gut with cellulolytic bacteria that enabled C. elegans to utilize cellulose, an otherwise indigestible substrate, as a carbon source. Cellulolytic bacteria as a community component in the worm gut can also support additional bacterial species with specialized roles, which we demonstrate by using Lactobacillus plantarum to protect C. elegans against Salmonella enterica infection. This work shows that engineered microbiome communities can be used to endow host organisms with novel functions, such as the ability to utilize alternate nutrient sources or to better fight pathogenic bacteria.

Conditional effects of state fear of negative evaluation on restrictive eating behaviors.

Fear of being evaluated negatively by others is a risk factor for the development of disordered eating. Specifically, trait level fear of negative evaluation (FNE) predicts disordered eating severity above other social anxiety traits. However, it remains unclear how state levels of this fear may impact eating behavior. The current study aimed to examine this risk factor in the context of state-level eating behavior. We hypothesized that: (a) elevated levels of state FNE would enhance the relationship between restraint and restriction and (b) we sought to explore the predictive nature of high trait FNE on restriction. Study procedures for N = 64 undergraduate students included assessment of dietary restraint, fear of negative evaluation, and hypothetical meal choice in the context of several proposed social and non-social settings. Results indicated that higher state FNE was related to more restrictive food choice across settings, and levels of trait FNE were not related to food choices. State FNE did not enhance the relationship between restraint and restriction. This project sought to examine the degree to which fear of negative evaluation impacts the relationship between dietary restraint and restriction, testing a unique risk factor for the development of eating psychopathology.

A network-based approach for isolating the chronic inflammation gene signatures underlying complex diseases towards finding new treatment opportunities.

Complex diseases are associated with a wide range of cellular, physiological, and clinical phenotypes. To advance our understanding of disease mechanisms and our ability to treat these diseases, it is critical to delineate the molecular basis and therapeutic avenues of specific disease phenotypes, especially those that are associated with multiple diseases. Inflammatory processes constitute one such prominent phenotype, being involved in a wide range of health problems including ischemic heart disease, stroke, cancer, diabetes mellitus, chronic kidney disease, non-alcoholic fatty liver disease, and autoimmune and neurodegenerative conditions. While hundreds of genes might play a role in the etiology of each of these diseases, isolating the genes involved in the specific phenotype (e.g., inflammation "component") could help us understand the genes and pathways underlying this phenotype across diseases and predict potential drugs to target the phenotype. Here, we present a computational approach that integrates gene interaction networks, disease-/trait-gene associations, and drug-target information to accomplish this goal. We apply this approach to isolate gene signatures of complex diseases that correspond to chronic inflammation and use SAveRUNNER to prioritize drugs to reveal new therapeutic opportunities.

Eating Disorder Examination-Questionnaire and Clinical Impairment Assessment norms for intersectional identities using an MTurk sample.

OBJECTIVE: There are limited data to guide the interpretation of scores on measures of eating-disorder psychopathology among underrepresented individuals. We aimed to provide norms for the Eating Disorder Examination-Questionnaire (EDE-Q) and Clinical Impairment Assessment (CIA) across racial/ethnic, gender, and sexual identities, and sexual orientations and their intersections by recruiting a diverse sample of Amazon MTurk workers (MTurkers; N = 1782). METHOD: We created a comprehensive, quantitative assessment of racial/ethnic identification, gender identification, sex assigned at birth, current sexual identification, and sexual orientation called the Demographic Assessment of Racial, Sexual, and Gender Identities (DARSGI). We calculated normative data for each demographic category response option. RESULTS: Our sample was comprised of 68% underrepresented racial/ethnic identities, 42% underrepresented gender identities, 13% underrepresented sexes, and 49% underrepresented sexual orientations. We reported means and standard deviations for each demographic category response option and, where possible, mean estimates by percentile across intersectional groups. EDE-Q Global Score for a subset of identities and intersections in the current study were higher than previously reported norms for those identities/intersections. DISCUSSION: This is the most thorough reporting of norms for the EDE-Q and CIA among racial/ethnic, sexual, and gender identities, and sexual orientations and the first reporting on multiple intersections, filling some of the gaps for commonly used measures of eating-disorder psychopathology. These norms may be used to contextualize eating-disorder psychopathology reported by underrepresented individuals. The data from the current study may help inform research on the prevention and treatment of eating-disorder psychopathology in underrepresented groups. PUBLIC SIGNIFICANCE: We provide the most thorough reporting on racial/ethnic, sexual, and gender identities, and sexual orientations for the Eating Disorder Examination - Questionnaire and Clinical Impairment Assessment, and the first reporting on intersections, which fills some of the gaps for commonly used measures of eating-disorder psychopathology. These norms help inform research on the prevention and treatment of eating-disorder psychopathology in underrepresented groups.

Development and validation of a scale for the tendency to exercise in response to mood, eating, and body image cues: the Reactive Exercise Scale (RES).

PURPOSE: Earlier work on engaging in physical exercise when experiencing negative affect demonstrated robust associations with eating disorder (ED) behaviors and attitudes; however, measurement of the behavior was primitive, relying on one yes/no question that cannot capture much variability. We report on the development of a self-report measure, the Reactive Exercise Scale (RES), that disentangles the tendency to engage in exercise in response to negative mood cues from the tendency to engage in exercise in response to eating and body image cues, which themselves may be associated with negative mood. The measure also assesses exercising in response to positive mood cues. METHODS: Exploratory factor analysis (EFA) guided item and factor selection. Confirmatory factor analysis (CFA) in an independent sample tested a 3-factor solution-exercising in response to negative mood cues, eating and body image cues, and positive mood cues. Correlations with exercise attitudes, eating disorder and body image attitudes, mood, and personality were used to evaluate construct validity. RESULTS: Results supported the 3-factor structure and indicated that exercising in response to negative mood cues may not uniquely relate to most aspects of ED psychopathology when accounting for eating and body image cues, which themselves are associated with negative mood. CONCLUSION: The RES captures the tendency to exercise in response to negative mood, positive mood, and eating and body image cues. Together, these constructs allow researchers to examine the unique relations of negative mood cued exercise with ED constructs, while accounting for appearance-related motives for which exercise may also be used. LEVEL OF EVIDENCE: Level III: evidence obtained from well-designed cohort or case-control analytic studies.

GenePlexus: a web-server for gene discovery using network-based machine learning.

Biomedical researchers take advantage of high-throughput, high-coverage technologies to routinely generate sets of genes of interest across a wide range of biological conditions. Although these technologies have directly shed light on the molecular underpinnings of various biological processes and diseases, the list of genes from any individual experiment is often noisy and incomplete. Additionally, interpreting these lists of genes can be challenging in terms of how they are related to each other and to other genes in the genome. In this work, we present GenePlexus (https://www.geneplexus.net/), a web-server that allows a researcher to utilize a powerful, network-based machine learning method to gain insights into their gene set of interest and additional functionally similar genes. Once a user uploads their own set of human genes and chooses between a number of different human network representations, GenePlexus provides predictions of how associated every gene in the network is to the input set. The web-server also provides interpretability through network visualization and comparison to other machine learning models trained on thousands of known process/pathway and disease gene sets. GenePlexus is free and open to all users without the need for registration.

Eighteen-month Course and Outcome of Adolescent Restrictive Eating Disorders: Persistence, Crossover, and Recovery.

OBJECTIVE: In adults, low-weight restrictive eating disorders, including anorexia nervosa (AN), are marked by chronicity and diagnostic crossover from restricting to binge-eating/purging. Less is known about the naturalistic course of these eating disorders in adolescents, particularly atypical AN (atyp-AN) and avoidant/restrictive food intake disorder (ARFID). To inform nosology of low-weight restrictive eating disorders in adolescents, we examined outcomes including persistence, crossover, and recovery in an 18-month observational study. METHOD: We assessed 82 women (ages 10-23 years) with low-weight eating disorders including AN (n = 40; 29 restricting, 11 binge-eating/purging), atyp-AN (n = 26; 19 restricting, seven binge-eating/purging), and ARFID (n = 16) at baseline, nine months (9 M; 75% retention), and 18 months (18 M; 73% retention) via semi-structured interviews. First-order Markov modeling was used to determine diagnostic persistence, crossover, and recovery occurring at 9 M or 18 M. RESULTS: Among all diagnoses, the likelihood of remaining stable within a given diagnosis was greater than that of transitioning, with the greatest probability among ARFID (0.84) and AN-R (0.62). Persistence of BP and atypical presentations at follow-up periods was less stable (AN-BP probability 0.40; atyp-AN-R probability 0.48; atyp-AN-BP probability, 0.50). Crossover from binge-eating/purging to restricting occurred 72% of the time; crossover from restricting to binge-eating/purging occurred 23% of the time. The likelihood of stable recovery (e.g., recovery at both 9 M and 18 M) was between 0.00 and 0.36. CONCLUSION: Across groups, intake diagnosis persisted in about two-thirds, and recovery was infrequent, underscoring the urgent need for innovative treatment approaches to these illnesses. Frequent crossover between AN and atyp-AN supports continuity between typical and atypical presentations, whereas no crossover to ARFID supports its distinction.