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Abstract Background Network Component Analysis (NCA) has shown its effectiveness in discovering regulators and inferring transcription factor activities (TFAs) when both microarray data and ChIP-on-chip data are available. However, a NCA scheme is not applicable to many biological studies due to limited topology information available, such as lack of ChIP-on-chip data. We propose a new approach, motif-directed NCA (mNCA), to integrate motif information and gene expression data to infer regulatory networks. Results We develop motif-directed NCA (mNCA) to incorporate motif information into NCA for regulatory network inference. While motif information is readily available from knowledge databases, it is a "noisy" source of network topology information consisting of many false positives. To overcome this problem, we develop a stability analysis procedure embedded in mNCA to resolve the inconsistency between motif information and gene expression data, and to enable the identification of stable TFAs. The mNCA approach has been applied to a time course microarray data set of muscle regeneration. The experimental results show that the inferred TFAs are not only numerically stable but also biologically relevant to muscle differentiation process. In particular, several inferred TFAs like those of MyoD, myogenin and YY1 are well supported by biological experiments. Conclusion A novel computational approach, mNCA, has been developed to integrate motif information and gene expression data for regulatory network reconstruction. Specifically, motif analysis is used to obtain initial network topology, and stability analysis is developed and applied with mNCA to extract stable TFAs. Experimental results on muscle regeneration microarray data have demonstrated that mNCA is a practical and reliable computational method for regulatory network inference and pathway discovery.

Abstract Background Recycling of endosomes is important for trafficking and maintenance of proteins at the neuromuscular junction (NMJ). We have previously shown high expression of the endocytic recycling regulator Eps15 homology domain-containing (EHD)1 proteinin the Torpedo californica electric organ, a model tissue for investigating a cholinergic synapse. In this study, we investigated the localization of EHD1 and its paralogs EHD2, EHD3, and EHD4 in mouse skeletal muscle, and assessed the morphological changes in EHD1−/− NMJs. Methods Localization of the candidate NMJ protein EHD1 was assessed by confocal microscopy analysis of whole-mount mouse skeletal muscle fibers after direct gene transfer and immunolabeling. The potential function of EHD1 was assessed by specific force measurement and α-bungarotoxin-based endplate morphology mapping in EHD1−/− mouse skeletal muscle. Results Endogenous EHD1 localized to primary synaptic clefts of murine NMJ, and this localization was confirmed by expression of recombinant green fluorescent protein labeled-EHD1 in murine skeletal muscle in vivo. EHD1−/− mouse skeletal muscle had normal histology and NMJ morphology, and normal specific force generation during muscle contraction. The EHD 1–4 proteins showed differential localization in skeletal muscle: EHD2 to muscle vasculature, EHD3 to perisynaptic regions, and EHD4 to perinuclear regions and to primary synaptic clefts, but at lower levels than EHD1. Additionally, specific antibodies raised against mammalian EHD1-4 recognized proteins of the expected mass in the T. californica electric organ. Finally, we found that EHD4 expression was more abundant in EHD1−/− mouse skeletal muscle than in wild-type skeletal muscle. Conclusion EHD1 and EHD4 localize to the primary synaptic clefts of the NMJ. Lack of obvious defects in NMJ structure and muscle function in EHD1−/− muscle may be due to functional compensation by other EHD paralogs.

Abstract Background Duchenne muscular dystrophy is a genetic disease involving a severe muscle wasting that is characterized by cycles of muscle degeneration/regeneration and culminates in early death in affected boys. Mitochondria are presumed to be involved in the regulation of myoblast proliferation/differentiation; enhancing mitochondrial activity with exercise mimetics (AMPK and PPAR-delta agonists) increases muscle function and inhibits muscle wasting in healthy mice. We therefore asked whether metabolic remodeling agents that increase mitochondrial activity would improve muscle function in mdx mice. Methods Twelve-week-old mdx mice were treated with two different metabolic remodeling agents (GW501516 and AICAR), separately or in combination, for 4 weeks. Extensive systematic behavioral, functional, histological, biochemical, and molecular tests were conducted to assess the drug(s)' effects. Results We found a gain in body and muscle weight in all treated mice. Histologic examination showed a decrease in muscle inflammation and in the number of fibers with central nuclei and an increase in fibers with peripheral nuclei, with significantly fewer activated satellite cells and regenerating fibers. Together with an inhibition of FoXO1 signaling, these results indicated that the treatments reduced ongoing muscle damage. Conclusions The three treatments produced significant improvements in disease phenotype, including an increase in overall behavioral activity and significant gains in forelimb and hind limb strength. Our findings suggest that triggering mitochondrial activity with exercise mimetics improves muscle function in dystrophin-deficient mdx mice.

Abstract Background Somatic Copy Number Alterations (CNAs) in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC), a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1) exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2) performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3) iteratively detecting Significant Copy Number Aberrations (SCAs) and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme. Results We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS) on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma). When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC) or tumor suppressor genes (e.g., CDKN2A/B). Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies. Conclusions Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes. Open–source and platform-independent SAIC software is implemented using C++, together with R scripts for data formatting and Perl scripts for user interfacing, and it is easy to install and efficient to use. The source code and documentation are freely available at http://www.cbil.ece.vt.edu/software.htm.

Abstract Background Spinal cord injury (SCI) induces secondary tissue damage that is associated with inflammation. We have previously demonstrated that inflammation-related gene expression after SCI occurs in two waves - an initial cluster that is acutely and transiently up-regulated within 24 hours, and a more delayed cluster that peaks between 72 hours and 7 days. Here we extend the microarray analysis of these gene clusters up to 6 months post-SCI. Methods Adult male rats were subjected to mild, moderate or severe spinal cord contusion injury at T9 using a well-characterized weight-drop model. Tissue from the lesion epicenter was obtained 4 hours, 24 hours, 7 days, 28 days, 3 months or 6 months post-injury and processed for microarray analysis and protein expression. Results Anchor gene analysis using C1qB revealed a cluster of genes that showed elevated expression through 6 months post-injury, including galectin-3, p22PHOX, gp91PHOX, CD53 and progranulin. The expression of these genes occurred primarily in microglia/macrophage cells and was confirmed at the protein level using both immunohistochemistry and western blotting. As p22PHOX and gp91PHOX are components of the NADPH oxidase enzyme, enzymatic activity and its role in SCI were assessed and NADPH oxidase activity was found to be significantly up-regulated through 6 months post-injury. Further, treating rats with the nonspecific, irreversible NADPH oxidase inhibitor diphenylene iodinium (DPI) reduced both lesion volume and expression of chronic gene cluster proteins one month after trauma. Conclusions These data demonstrate that inflammation-related genes are chronically up-regulated after SCI and may contribute to further tissue loss.

Abstract Background During development, the branchial mesoderm of Torpedo californica transdifferentiates into an electric organ capable of generating high voltage discharges to stun fish. The organ contains a high density of cholinergic synapses and has served as a biochemical model for the membrane specialization of myofibers, the neuromuscular junction (NMJ). We studied the genome and proteome of the electric organ to gain insight into its composition, to determine if there is concordance with skeletal muscle and the NMJ, and to identify novel synaptic proteins. Results Of 435 proteins identified, 300 mapped to Torpedo cDNA sequences with ≥2 peptides. We identified 14 uncharacterized proteins in the electric organ that are known to play a role in acetylcholine receptor clustering or signal transduction. In addition, two human open reading frames, C1orf123 and C6orf130, showed high sequence similarity to electric organ proteins. Our profile lists several proteins that are highly expressed in skeletal muscle or are muscle specific. Synaptic proteins such as acetylcholinesterase, acetylcholine receptor subunits, and rapsyn were present in the electric organ proteome but absent in the skeletal muscle proteome. Conclusions Our integrated genomic and proteomic analysis supports research describing a muscle-like profile of the organ. We show that it is a repository of NMJ proteins but we present limitations on its use as a comprehensive model of the NMJ. Finally, we identified several proteins that may become candidates for signaling proteins not previously characterized as components of the NMJ.

Abstract Background Cardiomyopathy in Duchenne muscular dystrophy (DMD) is an increasing cause of death in patients. The absence of dystrophin leads to loss of membrane integrity, cell death and fibrosis in cardiac muscle. Treatment of cardiomyocyte membrane instability could help prevent cardiomyopathy. Methods Three month old female mdx mice were exposed to the β1 receptor agonist isoproterenol subcutaneously and treated with the non-ionic tri-block copolymer Poloxamer P188 (P188) (460 mg/kg/dose i.p. daily). Cardiac function was assessed using high frequency echocardiography. Tissue was evaluated with Evans Blue Dye (EBD) and picrosirius red staining. Results BL10 control mice tolerated 30 mg/kg/day of isoproterenol for 4 weeks while death occurred in mdx mice at 30, 15, 10, 5 and 1 mg/kg/day within 24 hours. Mdx mice tolerated a low dose of 0.5 mg/kg/day. Isoproterenol exposed mdx mice showed significantly increased heart rates (p < 0.02) and cardiac fibrosis (p < 0.01) over 4 weeks compared to unexposed controls. P188 treatment of mdx mice significantly increased heart rate (median 593 vs. 667 bpm; p < 0.001) after 2 weeks and prevented a decrease in cardiac function in isoproterenol exposed mice (Shortening Fraction = 46 ± 6% vs. 35 ± 6%; p = 0.007) after 4 weeks. P188 treated mdx mice did not show significant differences in cardiac fibrosis, but demonstrated significantly increased EBD positive fibers. Conclusions This model suggests that chronic intermittent intraperitoneal P188 treatment can prevent isoproterenol induced cardiomyopathy in dystrophin deficient mdx mice.

Abstract Background Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated. Results We propose a novel approach, motif-guided sparse decomposition (mSD), to identify gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1) transcription factor activity and (2) the strength of the predicted gene regulation event(s). Specifically, a motif-guided clustering method is first developed to estimate the transcription factor activity of a gene module; sparse component analysis is then applied to estimate the regulation strength, and so predict the target genes of the transcription factors. The mSD approach was first tested for its improved performance in finding regulatory modules using simulated and real yeast data, revealing functionally distinct gene modules enriched with biologically validated transcription factors. We then demonstrated the efficacy of the mSD approach on breast cancer cell line data and uncovered several important gene regulatory modules related to endocrine therapy of breast cancer. Conclusion We have developed a new integrated strategy, namely motif-guided sparse decomposition (mSD) of gene expression data, for regulatory module identification. The mSD method features a novel motif-guided clustering method for transcription factor activity estimation by finding a balance between co-regulation and co-expression. The mSD method further utilizes a sparse decomposition method for regulation strength estimation. The experimental results show that such a motif-guided strategy can provide context-specific regulatory modules in both yeast and breast cancer studies.

Abstract Background The molecular mechanisms underlying the sex differences in human muscle morphology and function remain to be elucidated. The sex differences in the skeletal muscle transcriptome in both the resting state and following anabolic stimuli, such as resistance exercise (RE), might provide insight to the contributors of sexual dimorphism of muscle phenotypes. We used microarrays to profile the transcriptome of the biceps brachii of young men and women who underwent an acute unilateral RE session following 12 weeks of progressive training. Bilateral muscle biopsies were obtained either at an early (4 h post-exercise) or late recovery (24 h post-exercise) time point. Muscle transcription profiles were compared in the resting state between men (n = 6) and women (n = 8), and in response to acute RE in trained exercised vs. untrained non-exercised control muscle for each sex and time point separately (4 h post-exercise, n = 3 males, n = 4 females; 24 h post-exercise, n = 3 males, n = 4 females). A logistic regression-based method (LRpath), following Bayesian moderated t-statistic (IMBT), was used to test gene functional groups and biological pathways enriched with differentially expressed genes. Results This investigation identified extensive sex differences present in the muscle transcriptome at baseline and following acute RE. In the resting state, female muscle had a greater transcript abundance of genes involved in fatty acid oxidation and gene transcription/translation processes. After strenuous RE at the same relative intensity, the time course of the transcriptional modulation was sex-dependent. Males experienced prolonged changes while females exhibited a rapid restoration. Most of the biological processes involved in the RE-induced transcriptional regulation were observed in both males and females, but sex specificity was suggested for several signaling pathways including activation of notch signaling and TGF-beta signaling in females. Sex differences in skeletal muscle transcriptional regulation might implicate a mechanism behind disproportional muscle growth in males as compared with female counterparts after RE training at the same relative intensity. Conclusions Sex differences exist in skeletal muscle gene transcription both at rest and following acute RE, suggesting that sex is a significant modifier of the transcriptional regulation in skeletal muscle. The findings from the present study provide insight into the molecular mechanisms for sex differences in muscle phenotypes and for muscle transcriptional regulation associated with training adaptations to resistance exercise.

Abstract Background Numerous studies have demonstrated associations between genetic markers and COPD, but results have been inconsistent. One reason may be heterogeneity in disease definition. Unsupervised learning approaches may assist in understanding disease heterogeneity. Methods We selected 31 phenotypic variables and 12 SNPs from five candidate genes in 308 subjects in the National Emphysema Treatment Trial (NETT) Genetics Ancillary Study cohort. We used factor analysis to select a subset of phenotypic variables, and then used cluster analysis to identify subtypes of severe emphysema. We examined the phenotypic and genotypic characteristics of each cluster. Results We identified six factors accounting for 75% of the shared variability among our initial phenotypic variables. We selected four phenotypic variables from these factors for cluster analysis: 1) post-bronchodilator FEV1 percent predicted, 2) percent bronchodilator responsiveness, and quantitative CT measurements of 3) apical emphysema and 4) airway wall thickness. K-means cluster analysis revealed four clusters, though separation between clusters was modest: 1) emphysema predominant, 2) bronchodilator responsive, with higher FEV1; 3) discordant, with a lower FEV1 despite less severe emphysema and lower airway wall thickness, and 4) airway predominant. Of the genotypes examined, membership in cluster 1 (emphysema-predominant) was associated with TGFB1 SNP rs1800470. Conclusions Cluster analysis may identify meaningful disease subtypes and/or groups of related phenotypic variables even in a highly selected group of severe emphysema subjects, and may be useful for genetic association studies.

Abstract Background In cancer, gene networks and pathways often exhibit dynamic behavior, particularly during the process of carcinogenesis. Thus, it is important to prioritize those genes that are strongly associated with the functionality of a network. Traditional statistical methods are often inept to identify biologically relevant member genes, motivating researchers to incorporate biological knowledge into gene ranking methods. However, current integration strategies are often heuristic and fail to incorporate fully the true interplay between biological knowledge and gene expression data. Results To improve knowledge-guided gene ranking, we propose a novel method called coordinative component analysis (COCA) in this paper. COCA explicitly captures those genes within a specific biological context that are likely to be expressed in a coordinative manner. Formulated as an optimization problem to maximize the coordinative effort, COCA is designed to first extract the coordinative components based on a partial guidance from knowledge genes and then rank the genes according to their participation strengths. An embedded bootstrapping procedure is implemented to improve statistical robustness of the solutions. COCA was initially tested on simulation data and then on published gene expression microarray data to demonstrate its improved performance as compared to traditional statistical methods. Finally, the COCA approach has been applied to stem cell data to identify biologically relevant genes in signaling pathways. As a result, the COCA approach uncovers novel pathway members that may shed light into the pathway deregulation in cancers. Conclusion We have developed a new integrative strategy to combine biological knowledge and microarray data for gene ranking. The method utilizes knowledge genes for a guidance to first extract coordinative components, and then rank the genes according to their contribution related to a network or pathway. The experimental results show that such a knowledge-guided strategy can provide context-specific gene ranking with an improved performance in pathway member identification.

Abstract Background Prednisone, one of the most highly prescribed drugs, has well characterized effects on gene transcription mediated by the glucocorticoid receptor. These effects are typically occurring on the scale of hours. Prednisone also has a number of non-transcriptional effects (occurring on minutes scale) on protein signaling, yet these are less well studied. We sought to expand the understanding of acute effects of prednisone action on cell signaling using a combination of SILAC strategy and subcellular fractionations from C2C12 myotubes. Results De novo translation of proteins was inhibited in both SILAC labeled and unlabeled C2C12 myotubes. Unlabeled cells were exposed to prednisone while SILAC labeled cells remained untreated. After 0, 5, 15, and 30 minutes of prednisone exposure, labeled and unlabeled cells were mixed at 1:1 ratios and fractionated into cytosolic and nuclear fractions. A total of 534 proteins in the cytosol and 626 proteins in the nucleus were identified and quantitated, using 3 or more peptides per protein with peptide based probability ≤ 0.001. We identified significant increases (1.7- to 3.1- fold) in cytoplasmic abundance of 11 ribosomal proteins within 5 minutes of exposure, all of which returned to baseline by 30 min. We hypothesized that these drug-induced acute changes in the subcellular localization of the cell's protein translational machinery could lead to altered translation of quiescent RNAs. To test this, de novo protein synthesis was assayed after 15 minutes of drug exposure. Quantitative fluorography identified 16 2D gel spots showing rapid changes in translation; five of these were identified by MS/MS (pyruvate kinase, annexin A6 isoform A and isoform B, nasopharyngeal epithelium specific protein 1, and isoform 2 of Replication factor C subunit 1), and all showed the 5' terminal oligopyrimidine motifs associated with mRNA sequestration to and from inactive mRNA pools. Conclusion We describe novel approaches of subcellular proteomic profiling and assessment of acute changes on a minute-based time scale. These data expand the current knowledge of acute, non-transcriptional activities of glucocorticoids, including changes in protein subcellular localization, altered translation of quiescent RNA pools, and PKC-mediated cytoskeleton remodeling.

Abstract Background A common SNP upstream of the INSIG2 gene, rs7566605 (g.-10,1025G>C, Chr2:118,552,255, NT_022135.15), was reported to be associated with obesity (Body Mass Index, [BMI]) in a genome-wide association scan using the Framingham Heart Study but has not been reproduced in other cohorts. As BMI is a relatively insensitive measure of adiposity that is subject to many confounding variables, we sought to determine the relationship between the INSIG2 SNP and subcutaneous fat volumes measured by MRI in a young adult population. Methods We genotyped the INSIG2 SNP rs7566605 in college-aged population enrolled in a controlled resistance-training program, (the Functional Polymorphism Associated with Human Muscle Size and Strength, FAMuSS cohort, n = 752 volunteers 18–40 yrs). In this longitudinal study, we examined the effect of the INSIG2 polymorphism on subcutaneous fat and muscle volumes of the upper arm measured by magnetic resonance imaging (MRI) before and after 12 wks of resistance training. Gene/phenotype associations were tested using an analysis of covariance model with age and weight as covariates. Further, the % variation in each phenotype attributable to genotype was determined using hierarchical models and tested with a likelihood ratio test. Results Women with a copy of the C allele had higher levels of baseline subcutaneous fat (GG: n = 139; 243473 ± 5713 mm3 vs. GC/CC: n = 181; 268521 ± 5003 mm3; p = 0.0011); but men did not show any such association. Men homozygous for the G ancestral allele showed a loss of subcutaneous fat, while those with one or two copies of the C allele gained a greater percentage of subcutaneous fat with resistance training (GG: n = 103; 1.02% ± 1.74% vs. GC/CC: n = 93; 6.39% ± 1.82%; p = 0.035). Conclusion Our results show that the INSIG2 rs7566605 polymorphism underlies variation in subcutaneous adiposity in young adult women and suppresses the positive effects of resistance training on men. This supports and extends the original finding that there is an association between measures of obesity and INSIG2 rs7566605 and further implicates this polymorphism in fat regulation.

Abstract Background Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical methods often fail to identify biologically meaningful biomarkers related to a specific disease under study. In this paper, we develop a novel strategy, namely knowledge-guided multi-scale independent component analysis (ICA), to first infer regulatory signals and then identify biologically relevant biomarkers from microarray data. Results Since gene expression levels reflect the joint effect of several underlying biological functions, disease-specific biomarkers may be involved in several distinct biological functions. To identify disease-specific biomarkers that provide unique mechanistic insights, a meta-data "knowledge gene pool" (KGP) is first constructed from multiple data sources to provide important information on the likely functions (such as gene ontology information) and regulatory events (such as promoter responsive elements) associated with potential genes of interest. The gene expression and biological meta data associated with the members of the KGP can then be used to guide subsequent analysis. ICA is then applied to multi-scale gene clusters to reveal regulatory modes reflecting the underlying biological mechanisms. Finally disease-specific biomarkers are extracted by their weighted connectivity scores associated with the extracted regulatory modes. A statistical significance test is used to evaluate the significance of transcription factor enrichment for the extracted gene set based on motif information. We applied the proposed method to yeast cell cycle microarray data and Rsf-1-induced ovarian cancer microarray data. The results show that our knowledge-guided ICA approach can extract biologically meaningful regulatory modes and outperform several baseline methods for biomarker identification. Conclusion We have proposed a novel method, namely knowledge-guided multi-scale ICA, to identify disease-specific biomarkers. The goal is to infer knowledge-relevant regulatory signals and then identify corresponding biomarkers through a multi-scale strategy. The approach has been successfully applied to two expression profiling experiments to demonstrate its improved performance in extracting biologically meaningful and disease-related biomarkers. More importantly, the proposed approach shows promising results to infer novel biomarkers for ovarian cancer and extend current knowledge.

Abstract Background The main limitations of most existing clustering methods used in genomic data analysis include heuristic or random algorithm initialization, the potential of finding poor local optima, the lack of cluster number detection, an inability to incorporate prior/expert knowledge, black-box and non-adaptive designs, in addition to the curse of dimensionality and the discernment of uninformative, uninteresting cluster structure associated with confounding variables. Results In an effort to partially address these limitations, we develop the VIsual Statistical Data Analyzer (VISDA) for cluster modeling, visualization, and discovery in genomic data. VISDA performs progressive, coarse-to-fine (divisive) hierarchical clustering and visualization, supported by hierarchical mixture modeling, supervised/unsupervised informative gene selection, supervised/unsupervised data visualization, and user/prior knowledge guidance, to discover hidden clusters within complex, high-dimensional genomic data. The hierarchical visualization and clustering scheme of VISDA uses multiple local visualization subspaces (one at each node of the hierarchy) and consequent subspace data modeling to reveal both global and local cluster structures in a "divide and conquer" scenario. Multiple projection methods, each sensitive to a distinct type of clustering tendency, are used for data visualization, which increases the likelihood that cluster structures of interest are revealed. Initialization of the full dimensional model is based on first learning models with user/prior knowledge guidance on data projected into the low-dimensional visualization spaces. Model order selection for the high dimensional data is accomplished by Bayesian theoretic criteria and user justification applied via the hierarchy of low-dimensional visualization subspaces. Based on its complementary building blocks and flexible functionality, VISDA is generally applicable for gene clustering, sample clustering, and phenotype clustering (wherein phenotype labels for samples are known), albeit with minor algorithm modifications customized to each of these tasks. Conclusion VISDA achieved robust and superior clustering accuracy, compared with several benchmark clustering schemes. The model order selection scheme in VISDA was shown to be effective for high dimensional genomic data clustering. On muscular dystrophy data and muscle regeneration data, VISDA identified biologically relevant co-expressed gene clusters. VISDA also captured the pathological relationships among different phenotypes revealed at the molecular level, through phenotype clustering on muscular dystrophy data and multi-category cancer data.

Abstract Background Social insects dominate ecological communities because of their sophisticated group behaviors. However, the intricate behaviors of social insects may be exploited by social parasites, which manipulate insect societies for their own benefit. Interactions between social parasites and their hosts lead to unusual coevolutionary dynamics that ultimately affect the breeding systems and population structures of both species. This study represents one of the first attempts to understand the population and colony genetic structure of a parasite and its host in a social wasp system. Results We used DNA microsatellite markers to investigate gene flow, genetic variation, and mating behavior of the facultative social parasite Vespula squamosa and its primary host, V. maculifrons. Our analyses of genetic variability uncovered that both species possessed similar amounts of genetic variation and failed to show genetic structure over the sampling area. Our analysis of mating system of V. maculifrons and V. squamosa revealed high levels of polyandry and no evidence for inbreeding in the two species. Moreover, we found no significant differences between estimates of worker relatedness in this study and a previous investigation conducted over two decades ago, suggesting that the selective pressures operating on queen mate number have remained constant. Finally, the distribution of queen mate number in both species deviated from simple expectations suggesting that mate number may be under stabilizing selection. Conclusion The general biology of V. squamosa has not changed substantially from that of a typical, nonparasitic Vespula wasp. For example, population sizes of the host and its parasite appear to be similar, in contrast to other social parasites, which often display lower population sizes than their hosts. In addition, parasitism has not caused the mating behavior of V. squamosa queens to deviate from the high levels of multiple mating that typify Vespula wasps. This stands in contrast to some socially parasitic ants, which revert to mating with few males. Overall, the general similarity of the genetic structure of V. maculifrons and V. squamosa presumably reflects the fact that V. squamosa is still capable of independent colony founding and thus reflects an intermediate stage in the evolution of social parasitism.

Abstract Background We previously reported that NKG2A, a key inhibitory ligand for HLA-E, is expressed on activated TH2 but not TH1 cells. Here we measured cytokine expression in human ex vivo TH2 cells upon activation with anti-CD3/28 and challenge with an NKG2A-specific agonist. Methods TH2 cells were purified from healthy volunteers and activated with anti-CD3/28 in the presence and absence of NKG2A-specific agonist. IL-4 was used as a marker of TH2 effector function and measured by flow cytometry. Results Activation of TH2 cells increased NKG2A positivity from (Mean ± SE) 7.3 ± 2.4% to 13.7 ± 3.8%; (p = 0.03). The presence of NKG2A agonist did not significantly alter NKG2A expression, however, the percentage of activated TH2 cells expressing intracellular IL-4 decreased from 25.5 ± 6.8% to 9.3 ± 4.8% (p = 0.001). Conclusion We show that signalling through NKG2A suppresses TH2 effector function. This may provide a means to modulate Th1/Th2 balance in diseases where Th2 cytokines predominate.

Abstract Background Of the five sub-phenotypes defining metabolic syndrome, all are known to have strong genetic components (typically 50–80% of population variation). Studies defining genetic predispositions have typically focused on older populations with metabolic syndrome and/or type 2 diabetes. We hypothesized that the study of younger populations would mitigate many confounding variables, and allow us to better define genetic predisposition loci for metabolic syndrome. Methods We studied 610 young adult volunteers (average age 24 yrs) for metabolic syndrome markers, and volumetric MRI of upper arm muscle, bone, and fat pre- and post-unilateral resistance training. Results We found the PPARα L162V polymorphism to be a strong determinant of serum triglyceride levels in young White males, where carriers of the V allele showed 78% increase in triglycerides relative to L homozygotes (LL = 116 ± 11 mg/dL, LV = 208 ± 30 mg/dL; p = 0.004). Men with the V allele showed lower HDL (LL = 42 ± 1 mg/dL, LV = 34 ± 2 mg/dL; p = 0.001), but women did not. Subcutaneous fat volume was higher in males carrying the V allele, however, exercise training increased fat volume of the untrained arm in V carriers, while LL genotypes significantly decreased in fat volume (LL = -1,707 ± 21 mm3, LV = 17,617 ± 58 mm3 ; p = 0.002), indicating a systemic effect of the V allele on adiposity after unilateral training. Our study suggests that the primary effect of PPARα L162V is on serum triglycerides, with downstream effects on adiposity and response to training. Conclusion Our results on association of PPARα and triglycerides in males showed a much larger effect of the V allele than previously reported in older and less healthy populations. Specifically, we showed the V allele to increase triglycerides by 78% (p = 0.004), and this single polymorphism accounted for 3.8% of all variation in serum triglycerides in males (p = 0.0037).

Abstract Background Organisms are capable of developing different phenotypes by altering the genes they express. This phenotypic plasticity provides a means for species to respond effectively to environmental conditions. One of the most dramatic examples of phenotypic plasticity occurs in the highly social hymenopteran insects (ants, social bees, and social wasps), where distinct castes and sexes all arise from the same genes. To elucidate how variation in patterns of gene expression affects phenotypic variation, we conducted a study to simultaneously address the influence of developmental stage, sex, and caste on patterns of gene expression in Vespula wasps. Furthermore, we compared the patterns found in this species to those found in other taxa in order to investigate how variation in gene expression leads to phenotypic evolution. Results We constructed 11 different cDNA libraries derived from various developmental stages and castes of Vespula squamosa. Comparisons of overall expression patterns indicated that gene-expression differences distinguishing developmental stages were greater than expression differences differentiating sex or caste. Furthermore, we determined that certain sets of genes showed similar patterns of expression in the same phenotypic forms of different species. Specifically, larvae upregulated genes related to metabolism and genes possessing structural activity. Surprisingly, our data indicated that at least a few specific gene functions and at least one specific gene family are important components of caste differentiation across social insect taxa. Conclusion Despite research on various aspects of development originating from model systems, growth in understanding how development is related to phenotypic diversity relies on a growing literature of contrasting studies in non-model systems. In this study, we found that comparisons of patterns of gene expression with model systems highlighted areas of conserved and convergent developmental evolution across diverse taxa. Indeed, conserved biological functions across species implicated key functions related to how phenotypes are built. Finally, overall differences between social insect taxa suggest that the independent evolution of caste arose via distinct developmental trajectories.

Abstract Affymetrix microarrays have become a standard experimental platform for studies of mRNA expression profiling. Their success is due, in part, to the multiple oligonucleotide features (probes) against each transcript (probe set). This multiple testing allows for more robust background assessments and gene expression measures, and has permitted the development of many computational methods to translate image data into a single normalized "signal" for mRNA transcript abundance. There are now many probe set algorithms that have been developed, with a gradual movement away from chip-by-chip methods (MAS5), to project-based model-fitting methods (dCHIP, RMA, others). Data interpretation is often profoundly changed by choice of algorithm, with disoriented biologists questioning what the "accurate" interpretation of their experiment is. Here, we summarize the debate concerning probe set algorithms. We provide examples of how changes in mismatch weight, normalizations, and construction of expression ratios each dramatically change data interpretation. All interpretations can be considered as computationally appropriate, but with varying biological credibility. We also illustrate the performance of two new hybrid algorithms (PLIER, GC-RMA) relative to more traditional algorithms (dCHIP, MAS5, Probe Profiler PCA, RMA) using an interactive power analysis tool. PLIER appears superior to other algorithms in avoiding false positives with poorly performing probe sets. Based on our interpretation of the literature, and examples presented here, we suggest that the variability in performance of probe set algorithms is more dependent upon assumptions regarding "background", than on calculations of "signal". We argue that "background" is an enormously complex variable that can only be vaguely quantified, and thus the "best" probe set algorithm will vary from project to project.

Abstract Background Autoimmune diseases are more prevalent in females than in males, whereas males have higher mortality associated with infectious diseases. To increase our understanding of this sexual dimorphism in the immune system, we sought to identify and characterize inherent differences in immune response programs in the spleens of male and female mice before, during and after puberty. Results After the onset of puberty, female mice showed a higher expression of adaptive immune response genes, while males had a higher expression of innate immune genes. This result suggested a requirement for sex hormones. Using in vivo and in vitro assays in normal and mutant mouse strains, we found that reverse signaling through FasL was directly influenced by estrogen, with downstream consequences of increased CD8+ T cell-derived B cell help (via cytokines) and enhanced immunoglobulin production. Conclusion These results demonstrate that sexual dimorphism in innate and adaptive immune genes is dependent on puberty. This study also revealed that estrogen influences immunoglobulin levels in post-pubertal female mice via the Fas-FasL pathway.

Abstract Background We describe the development, validation, and use of a highly redundant 120,000 oligonucleotide microarray (MuscleChip) containing 4,601 probe sets representing 1,150 known genes expressed in muscle and 2,075 EST clusters from a non-normalized subtracted muscle EST sequencing project (28,074 EST sequences). This set included 369 novel EST clusters showing no match to previously characterized proteins in any database. Each probe set was designed to contain 20–32 25 mer oligonucleotides (10–16 paired perfect match and mismatch probe pairs per gene), with each probe evaluated for hybridization kinetics (Tm) and similarity to other sequences. The 120,000 oligonucleotides were synthesized by photolithography and light-activated chemistry on each microarray. Results Hybridization of human muscle cRNAs to this MuscleChip (33 samples) showed a correlation of 0.6 between the number of ESTs sequenced in each cluster and hybridization intensity. Out of 369 novel EST clusters not showing any similarity to previously characterized proteins, we focused on 250 EST clusters that were represented by robust probe sets on the MuscleChip fulfilling all stringent rules. 102 (41%) were found to be consistently "present" by analysis of hybridization to human muscle RNA, of which 40 ESTs (39%) could be genome anchored to potential transcription units in the human genome sequence. 19 ESTs of the 40 ESTs were furthermore computer-predicted as exons by one or more than three gene identification algorithms. Conclusion Our analysis found 40 transcriptionally validated, genome-anchored novel EST clusters to be expressed in human muscle. As most of these ESTs were low copy clusters (duplex and triplex) in the original 28,000 EST project, the identification of these as significantly expressed is a robust validation of the transcript units that permits subsequent focus on the novel proteins encoded by these genes.

Abstract Background We provide a systematic study of the sources of variability in expression profiling data using 56 RNAs isolated from human muscle biopsies (34 Affymetrix MuscleChip arrays), and 36 murine cell culture and tissue RNAs (42 Affymetrix U74Av2 arrays). Results We studied muscle biopsies from 28 human subjects as well as murine myogenic cell cultures, muscle, and spleens. Human MuscleChip arrays (4,601 probe sets) and murine U74Av2 Affymetrix microarrays were used for expression profiling. RNAs were profiled both singly, and as mixed groups. Variables studied included tissue heterogeneity, cRNA probe production, patient diagnosis, and GeneChip hybridizations. We found that the greatest source of variability was often different regions of the same patient muscle biopsy, reflecting variation in cell type content even in a relatively homogeneous tissue such as muscle. Inter-patient variation was also very high (SNP noise). Experimental variation (RNA, cDNA, cRNA, or GeneChip) was minor. Pre-profile mixing of patient cRNA samples effectively normalized both intra- and inter-patient sources of variation, while retaining a high degree of specificity of the individual profiles (86% of statistically significant differences detected by absolute analysis; and 85% by a 4-pairwise comparison survival method). Conclusions Using unsupervised cluster analysis and correlation coefficients of 92 RNA samples on 76 oligonucleotide microarrays, we found that experimental error was not a significant source of unwanted variability in expression profiling experiments. Major sources of variability were from use of small tissue biopsies, particularly in humans where there is substantial inter-patient variability (SNP noise).

Plastics are ubiquitous in our ecosystems, and microplastic accumulation in the environment is an emerging global health concern. Since available recycling technologies are not economically competitive with primary plastic production, global use is expected to reach 1231 megatons by 2060, with 493 megatons leeching into the environment each year. To identify new nylon-recycling biotechnologies, targeted genome mining was used to identify thermostable enzymes capable of degrading polyamides. Here, we describe the characterization of a novel protein sourced from Thermovenabulum gondwanense: TvgC. TvgC is extremely stable, exhibiting a melting temperature of 93 °C and no detectable losses in hydrolytic activity after one week at 60 °C. While nylonases primarily process nylon-6, TvgC catalysed the degradation of both nylon-6 and nylon-6,6 films, which are considerably more difficult to degrade. Finally, conversion experiments demonstrate that TvgC achieves a 1.2 wt % conversion of nylon-6 film, comparable to that of the most highly engineered nylonases. This novel hyperthermostable protein represents an excellent starting point for future engineering of increasingly efficient nylonases., (© 2024 The Author(s). Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

Flavonoids, known for their neuroprotective properties, are abundant in Acacia catechu and Scutellaria baicalensis. Yet, human studies on their combined effects are limited., Objective: This study evaluated the cognitive effects of combined Acacia catechu and Scutellaria baicalensis supplementation in healthy adults., Methods: In a randomized, double-blind, placebo-controlled trial, 26 males and 59 females ( N  = 85; 43 ± 8 yrs) consumed the test product (TP) containing 240 mg stem extract of Scutellaria baicalensis and 51 mg heartwood extract of Acacia catechu (UP326, Unigen, Tacoma, WA USA) or placebo (PLA) for four weeks. Cognitive function and biomarkers were assessed throughout the study., Results: Significant time effects ( p  < 0.001) were observed across cognitive function assessments, with no differences between groups. Energy and fatigue reports showed a significant time effect ( p  = 0.023), while no significant differences emerged in general health and well-being scores. Cortisol levels increased significantly over time across conditions ( p  = 0.005), but no significant changes were observed in change scores or individual visits. Interim ( p  = 0.023) and final ( p  = 0.004) absolute basophil levels differed significantly between groups, with no intergroup changes. No significant differences in BDNF, CRP, or health and safety biomarkers were detected between supplemental conditions or over time., Discussion: Four-week daily TP supplementation significantly enhanced cognitive function without difference from placebo. However, no adverse events or significant blood marker changes were noted, suggesting TP supplementation is generally well-tolerated. Further research is warranted to explore the preventive and attenuating cognitive effects of this supplementation. Trial registration: ISRCTN.org identifier: ISRCTN16548309.

Baeyer-Villiger monooxygenases (BVMOs) are NAD(P)H-dependent flavoproteins that convert ketones to esters and lactones. While these enzymes offer an appealing alternative to traditional Baeyer-Villiger oxidations, these proteins tend to be either too unstable or exhibit too narrow of a substrate scope for implementation as industrial biocatalysts. Here, sequence similarity networks were used to search for novel BVMOs that are both stable and promiscuous. Our genome mining led to the identification of an enzyme from Chloroflexota bacterium (strain G233) dubbed ssnBVMO that exhibits i) the highest melting temperature of any naturally sourced BVMO (62.5 °C), ii) a remarkable kinetic stability across a wide range of conditions, similar to those of PAMO and PockeMO, iii) optimal catalysis at 50 °C, and iv) a broad substrate scope that includes linear aliphatic, aromatic, and sterically bulky ketones. Subsequent quantitative assays using propiophenone demonstrated >95 % conversion. Several fusions were also constructed that linked ssnBVMO to a thermostable phosphite dehydrogenase. These fusions can recycle NADPH and catalyze oxidations with sub-stoichiometric quantities of this expensive cofactor. Characterization of these fusions permitted identification of PTDH-L1-ssnBVMO as the most promising protein that could have utility as a seed sequence for enzyme engineering campaigns aiming to develop biocatalysts for Baeyer-Villiger oxidations., (© 2024 The Authors. ChemBioChem published by Wiley-VCH GmbH.)

Compared with notifiable disease surveillance, claims-based algorithms estimate higher Lyme disease incidence, but their accuracy is unknown. We applied a previously developed Lyme disease algorithm (diagnosis code plus antimicrobial drug prescription dispensing within 30 days) to an administrative claims database in Massachusetts, USA, to identify a Lyme disease cohort during July 2000-June 2019. Clinicians reviewed and adjudicated medical charts from a cohort subset by using national surveillance case definitions. We calculated positive predictive values (PPVs). We identified 12,229 Lyme disease episodes in the claims database and reviewed and adjudicated 128 medical charts. The algorithm's PPV for confirmed, probable, or suspected cases was 93.8% (95% CI 88.1%-97.3%); the PPV was 66.4% (95% CI 57.5%-74.5%) for confirmed and probable cases only. In a high incidence setting, a claims-based algorithm identified cases with a high PPV, suggesting it can be used to assess Lyme disease burden and supplement traditional surveillance data.

Human nondisjunction errors in oocytes are the leading cause of pregnancy loss, and for pregnancies that continue to term, the leading cause of intellectual disabilities and birth defects. For the first time, we have conducted a candidate gene and genome-wide association study to identify genes associated with maternal nondisjunction of chromosome 21 as a first step to understand predisposing factors. A total of 2,186 study participants were genotyped on the HumanOmniExpressExome-8v1-2 array. These participants included 749 live birth offspring with standard trisomy 21 and 1,437 parents. Genotypes from the parents and child were then used to identify mothers with nondisjunction errors derived in the oocyte and to establish the type of error (meiosis I or meiosis II). We performed a unique set of subgroup comparisons designed to leverage our previous work suggesting that the etiologies of meiosis I and meiosis II nondisjunction differ for trisomy 21. For the candidate gene analysis, we selected genes associated with chromosome dynamics early in meiosis and genes associated with human global recombination counts. Several candidate genes showed strong associations with maternal nondisjunction of chromosome 21, demonstrating that genetic variants associated with normal variation in meiotic processes can be risk factors for nondisjunction. The genome-wide analysis also suggested several new potentially associated loci, although follow-up studies using independent samples are required., Competing Interests: The authors have declared that no competing interests exist.

Multiple field studies conducted for the Deployed War-Fighter Protection (DWFP) research program have generated more than 80 specific guidance points for innovative combinations of pesticide application equipment, pesticide formulations, and application techniques for aerosol and residual pesticide treatments in 6 ecological regions against a range of mosquito, sand fly, and filth fly nuisance and disease-vector threats. To synthesize and operationalize these DWFP field and laboratory efficacy data we developed an interactive iOS and Android mobile software application, the Pesticide App, consisting of specific pesticide application guidance organized by environment and target insect vector species.

This preliminary study surveyed the feeding practices of mothers with eating disorder histories through evaluation of mothers' reported feeding styles, child diet composition and restrictive special approaches to feeding. For this non-randomised cohort study, 25 mothers with eating disorder histories and 25 mothers with no history of an eating disorder with children ages 6-36 months were selected such that the groups were similar based on child age group and child sex. Mothers were compared on self-reported feeding style using the Infant Feeding Styles Questionnaire and on child diet composition and special feeding approaches using a modified version of the Toddler Diet Questionnaire from the Women, Infants, and Children program. Mothers with eating disorder histories scored lower on the restrictive feeding style subscale than controls. No significant differences were detected between groups in child diet including the percentage of mothers who breastfed, duration of breastfeeding, age at solid food introduction, daily number of meals or snacks or daily frequency of consumption of fruits, vegetables or protein foods. Mothers with eating disorder histories were more likely to report taking a restrictive special approach to feeding such as limiting processed foods or feeding organic foods only. Although mothers with eating disorder histories may not differ greatly from control mothers in terms of child diet composition (smaller effects may not have been detected due to limited sample size), they may be more likely to take restrictive special approaches to feeding which mirror dietary rules common in individuals with eating disorders., (© 2012 John Wiley & Sons Ltd.)

Objective: To describe the treatment development and pilot testing of a group parenting intervention, NURTURE (Networking, Uniting, and Reaching out To Upgrade Relationships and Eating), for mothers with histories of eating disorders., Method: Based on focus group findings, extant research, and expert opinion, NURTURE was designed to be delivered weekly over 16 (1.5 h) sessions via an interactive web conferencing forum. It comprises four modules: (1) laying the foundation, (2) general parenting skills, (3) eating and feeding, and (4) breaking the cycle of risk. Pilot testing was conducted with three groups of 3-6 mothers (N = 13) who had children ages 0-3 years to determine feasibility (e.g., retention), acceptability (e.g., feedback questionnaire responses), and preliminary efficacy. Maternal satisfaction with NURTURE and changes in mother-child feeding relationship measures, maternal feeding style, maternal self-efficacy, and maternal psychopathology (eating disorder, depression, and anxiety symptoms) across three time points (baseline, post-treatment, 6-month follow-up) were examined. All outcomes were exploratory., Results: The intervention was well tolerated with a 100% retention rate. Feedback from mothers was generally positive and indicated that the groups provided an engaging, supportive experience to participants. We observed changes suggestive of improvement in self-reported maternal self-efficacy and competence with parenting. There were no notable changes in measures of maternal feeding style or psychopathology., Discussion: NURTURE is a feasible, acceptable, and potentially valuable intervention for mothers with eating disorder histories. Results of this pilot will inform a larger randomized-controlled intervention to determine efficacy and impact on child outcomes., (Copyright © 2013 Wiley Periodicals, Inc.)

The aim of this pilot project was to describe maternal responsiveness during child feeding in mothers with eating disorder histories through the combined use of observational, self-report, and physiologic methods. For this non-randomized cohort pilot study, 25 mothers with histories of eating disorders and 25 mothers with no history of an eating disorder with children ages 6-36 months were selected such that the groups were similar based on child age group (within 6 months) and child sex. Maternal behavioral responsiveness to child cues was assessed by video-recording and behavioral coding of both a free-play and feeding episode. Physiologic engagement was assessed through measurement of respiratory sinus arrhythmia (RSA) reactivity during free-play and feeding episodes. No differences were detected in observed behavioral responsiveness during feeding or free-play in mothers with eating disorder histories compared with controls. Mothers with eating disorder histories did report more parenting stress, increased anxiety, and exhibited a blunted physiologic stress response (less RSA reactivity) during both feeding and free-play interactions with their children. These results support future larger-scale investigations of RSA reactivity in mothers with eating disorders.

Although oxytocin (OT) has the potential to be an informative biomarker of social functioning in patients with eating disorders, the burden of invasive blood draws or lumbar punctures limits OT study. Salivary and urinary OT measurements may be advantageous, as they require less invasive sampling techniques which could be conducted in a wider variety of settings. Yet, the degree to which the concentration of OT in these fluids is correlated with blood levels is uncertain, as is the impact of vomiting on salivary secretion of OT. Therefore, we compared contemporaneously sampled OT concentration in blood, saliva, and urine from twenty women acutely ill with anorexia nervosa. Salivary OT was positively correlated with plasma OT in patients with no history of self-induced vomiting (r=0.89), but correlation was lower in those with recent history of self-induced vomiting (r=0.42). Urinary and plasma OT were not well-correlated(r=0.13), suggesting preliminarily that collection of plasma OT remains the method of choice. Self-induced vomiting in eating disorders may limit the applicability of salivary sampling for OT., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Objective: To further refine our understanding of impulsivity, obsessions, and compulsions in anorexia nervosa (AN) by isolating which behaviours--binge eating, purging, or both--are associated with these features., Methods: We conducted regression analyses with binge eating, purging, and the interaction of binge eating with purging as individual predictors of scores for impulsivity, obsessions, and compulsions in two samples of women with AN (n = 1373)., Results: Purging, but not binge eating, was associated with higher scores on impulsivity, obsessions, and compulsions. Purging was also associated with worst eating rituals and with worst eating preoccupations., Conclusion: Our results suggest that purging, compared with binge eating, may be a stronger correlate of impulsivity, obsessions, and compulsions in AN., (Copyright © 2012 John Wiley & Sons, Ltd and Eating Disorders Association.)

Despite a high prevalence of menstrual irregularities, women with anorexia nervosa are becoming pregnant. The physical and psychological demands of pregnancy and motherhood can represent an immense challenge for women already struggling with the medical and psychological stress of an eating disorder. This article summarizes key issues related to reproduction in women with anorexia nervosa, highlighting the importance of preconception counseling, adequate gestational weight gain, and sufficient pre- and post-natal nutrition. Postpartum issues including eating disorder symptom relapse, weight loss, breastfeeding, and risk of perinatal depression and anxiety are also discussed.

Objective: To compare the frequency with which unplanned pregnancies occur in individuals with anorexia nervosa relative to women without eating disorders in the Norwegian Mother and Child Cohort Study., Method: In a sample of 62,060 women, 62 reported anorexia nervosa. Using data from a questionnaire completed by all participating mothers, we compared mother's age at birth and the frequency with which mothers reported their index pregnancy as being unplanned., Results: Women with anorexia nervosa were younger (26.2 years, standard deviation 4.76) than women with no eating disorder (29.9 years, standard deviation 4.60) at the time of birth. Significantly more women with anorexia nervosa (50.0%) reported unplanned pregnancy than women in the referent group (18.9%). After adjustment for maternal age and infertility treatment, the relative risk of unplanned pregnancy in individuals with anorexia nervosa was 2.11 (95% confidence interval 1.64-2.72). Induced abortion was also significantly more common in women with anorexia nervosa than referent women (24.2% compared with 14.6%)., Conclusion: The higher rate of unplanned pregnancy and abortion in women with anorexia nervosa is of clinical concern because absent or irregular menstruation may be misinterpreted as decreasing risk of pregnancy., Level of Evidence: II.