Utility of targeted gene sequencing to differentiate myeloid malignancies from other cytopenic conditions

The National Heart, Lung, and Blood Institute-funded National MDS Natural History Study (NCT02775383) is a prospective cohort study enrolling patients with cytopenia with suspected myelodysplastic syndromes (MDS) to evaluate factors associated with disease. Here, we sequenced 53 genes in bone marrow samples harvested from 1298 patients diagnosed with myeloid malignancy, including MDS and non-MDS myeloid malignancy or alternative marrow conditions with cytopenia based on concordance between independent histopathologic reviews (local, centralized, and tertiary to adjudicate disagreements when needed). We developed a novel 2-stage diagnostic classifier based on mutational profiles in 18 of 53 sequenced genes that were sufficient to best predict a diagnosis of myeloid malignancy and among those with a predicted myeloid malignancy, predict whether they had MDS. The classifier achieved a positive predictive value (PPV) of 0.84 and negative predictive value (NPV) of 0.8 with an area under the receiver operating characteristic curve (AUROC) of 0.85 when classifying patients as having myeloid vs no myeloid malignancy based on variant allele frequencies (VAFs) in 17 genes and a PPV of 0.71 and NPV of 0.64 with an AUROC of 0.73 when classifying patients as having MDS vs non-MDS malignancy based on VAFs in 10 genes. We next assessed how this approach could complement histopathology to improve diagnostic accuracy. For 99 of 139 (71%) patients (PPV of 0.83 and NPV of 0.65) with local and centralized histopathologic disagreement in myeloid vs no myeloid malignancy, the classifier-predicted diagnosis agreed with the tertiary pathology review (considered the internal gold standard).

Executive function improvement in response to meta-cognitive training in chronic mTBI / PTSD

Objective

We tested Goal Management Training (GMT), which has been recommended as an executive training protocol that may improve the deficits in the complex tasks inherent in life role participation experienced by those with chronic mild traumatic brain injury and post-traumatic stress disease (mTBI/PTSD). We assessed, not only cognitive function, but also life role participation (quality of life).

Methods

We enrolled and treated 14 individuals and administered 10 GMT sessions in-person and provided the use of the Veterans Task Manager (VTM), a Smartphone App, which was designed to serve as a "practice-buddy" device to ensure translation of in-person learning to independent home and community practice of complex tasks. Pre-/post-treatment primary measure was the NIH Examiner, Unstructured Task. Secondary measures were as follows: Tower of London time to complete (cTOL), Community Reintegration of Service Members (CRIS) three subdomains [Extent of Participation; Limitations; Satisfaction of Life Role Participation (Satisfaction)]. We analyzed pre-post-treatment, t-test models to explore change, and generated descriptive statistics to inspect given individual patterns of change across measures.

Results

There was statistically significant improvement for the NIH EXAMINER Unstructured Task (p < .02; effect size = .67) and cTOL (p < .01; effect size = .52. There was a statistically significant improvement for two CRIS subdomains: Extent of Participation (p < .01; effect size = .75; Limitations (p < .05; effect size = .59). Individuals varied in their treatment response, across measures.

Conclusions and Clinical Significance

In Veterans with mTBI/PTSD in response to GMT and the VTM learning support buddy, there was significant improvement in executive cognition processes, sufficiently robust to produce significant improvement in community life role participation. The individual variations support need for precision neurorehabilitation. The positive results occurred in response to treatment advantages afforded by the content of the combined GMT and the employment of the VTM learning support buddy, with advantages including the following: manualized content of the GMT; incremental complex task difficulty; GMT structure and flexibility to incorporate individualized functional goals; and the VTM capability of ensuring translation of in-person instruction to home and community practice, solidifying newly learned executive cognitive processes. Study results support future study, including a potential randomized controlled trial, the manualized GMT and availability of the VTM to ensure future clinical deployment of treatment, as warranted.

A pseudo-value regression approach for differential network analysis of co-expression data

BACKGROUND

The differential network (DN) analysis identifies changes in measures of association among genes under two or more experimental conditions. In this article, we introduce a pseudo-value regression approach for network analysis (PRANA). This is a novel method of differential network analysis that also adjusts for additional clinical covariates. We start from mutual information criteria, followed by pseudo-value calculations, which are then entered into a robust regression model.

RESULTS

This article assesses the model performances of PRANA in a multivariable setting, followed by a comparison to dnapath and DINGO in both univariable and multivariable settings through variety of simulations. Performance in terms of precision, recall, and F1 score of differentially connected (DC) genes is assessed. By and large, PRANA outperformed dnapath and DINGO, neither of which is equipped to adjust for available covariates such as patient-age. Lastly, we employ PRANA in a real data application from the Gene Expression Omnibus database to identify DC genes that are associated with chronic obstructive pulmonary disease to demonstrate its utility.

CONCLUSION

To the best of our knowledge, this is the first attempt of utilizing a regression modeling for DN analysis by collective gene expression levels between two or more groups with the inclusion of additional clinical covariates. By and large, adjusting for available covariates improves accuracy of a DN analysis.

Corrigendum: The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies

[This corrects the article DOI: 10.3389/fimmu.2022.1093242.].

Providing pharmacy support to housebound patients: learning from the COVID-19 pandemic

Introduction

Housebound patients may face challenges to their medicines management due to reduced household mobility and potential lack of access to healthcare services. Previous literature has explored the medication-related needs of housebound patients from pharmacists’ perspectives (1-2). However little work has focussed on the patient/family perspective. In this study, we used data obtained from those staying at home as much as possible during the COVID-19 pandemic to fill this gap.

Aim

To explore home medicine practices and safety for people who were housebound during the COVID19 pandemic and to create guidance, from the patient/family perspective, for enabling pharmacists to facilitate safe medicine practices for this population.

Methods

Interviews were carried out with people who were taking at least one long term medication and met the criteria for ‘shielding’ and/or were over 70 years of age during the first wave of the COVID-19 pandemic in the UK and/or their family carers. Respondents were recruited through patient and public involvement representatives, the research team’s networks, and support groups. Potential participants were approached via personal contact and social media. Interviews were conducted by telephone or video conferencing and participants asked about their medicines management while staying at home. Inductive thematic analysis was carried out. Patient and public involvement representatives were involved in the data analysis alongside the researchers.

Results

Fifty people were interviewed (16 males, 34 females; mean age 68 years, range 26–93 years). Interview data suggested diversity of experiences of medicines management while staying at home. Some respondents reported no or little change, others an initial crisis followed by re-stabilisation, and others that the pandemic was a tipping point, exacerbating underlying challenges and having negative effects on their health and wellbeing. Medicine safety issues reported included omitted doses and less-effective formulations being used. Participants also described experiencing high levels of anxiety related to obtaining medicines, monitoring medicines and feeling at risk of contracting COVID-19 while accessing medicine-related healthcare services. Key factors identified as facilitating a smooth transition included patients’ own agency, support from family, friends and community, good communication with pharmacy staff, continuity of pharmacy services and synchronisation of medicines supply so that a maximum of one collection/delivery was required each month.

Conclusion

The study findings that we have presented relate to the UK only; this may limit the generalisability of our findings to other countries. Findings from Ireland are in the process of being analysed and will provide a basis of comparison. In addition, more females took part than males, despite efforts to address this. However, our findings suggest pharmacy staff can support medicines management for people who are housebound by synchronisation of medicines supply, delivering medicines where possible, developing/raising awareness of alternative means of communication, providing continuity of pharmacy services and signposting any community support available.

References

(1) Kayyali R, Funnell G, Harrap N, Patel A. Can community pharmacy successfully bridge the gap in care for housebound patients? Research in Social and Administrative Pharmacy 2019;15:425-439.

(2) Latif A, Mandane B, Anderson E, Barraclough C, Travis S. Optimizing medicine use for people who are homebound: an evaluation of a pilot domiciliary Medicine Use Review (dMUR) service in England. Integr Pharm Res Pract 2018;7:33-40.

The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies

Introduction

Over the last decade, the field of systems vaccinology has emerged, in which high throughput transcriptomics and other omics assays are used to probe changes of the innate and adaptive immune system in response to vaccination. The goal of this study was to benchmark key technical and analytical parameters of RNA sequencing (RNA-seq) in the context of a multi-site, double-blind randomized vaccine clinical trial.

Methods

We collected longitudinal peripheral blood mononuclear cell (PBMC) samples from 10 subjects before and after vaccination with a live attenuated Francisella tularensis vaccine and performed RNA-Seq at two different sites using aliquots from the same sample to generate two replicate datasets (5 time points for 50 samples each). We evaluated the impact of (i) filtering lowly-expressed genes, (ii) using external RNA controls, (iii) fold change and false discovery rate (FDR) filtering, (iv) read length, and (v) sequencing depth on differential expressed genes (DEGs) concordance between replicate datasets. Using synthetic mRNA spike-ins, we developed a method for empirically establishing minimal read-count thresholds for maintaining fold change accuracy on a per-experiment basis. We defined a reference PBMC transcriptome by pooling sequence data and established the impact of sequencing depth and gene filtering on transcriptome representation. Lastly, we modeled statistical power to detect DEGs for a range of sample sizes, effect sizes, and sequencing depths.

Results and Discussion

Our results showed that (i) filtering lowly-expressed genes is recommended to improve fold-change accuracy and inter-site agreement, if possible guided by mRNA spike-ins (ii) read length did not have a major impact on DEG detection, (iii) applying fold-change cutoffs for DEG detection reduced inter-set agreement and should be used with caution, if at all, (iv) reduction in sequencing depth had a minimal impact on statistical power but reduced the identifiable fraction of the PBMC transcriptome, (v) after sample size, effect size (i.e. the magnitude of fold change) was the most important driver of statistical power to detect DEG. The results from this study provide RNA sequencing benchmarks and guidelines for planning future similar vaccine studies.

Trajectories of stroke recovery of impairment, function, and quality of life in response to 12-month mobility and fitness intervention

BACKGROUND

Gait deficits and functional disability are persistent problems for many stroke survivors, even after standard neurorehabilitation. There is little quantified information regarding the trajectories of response to a long-dose, 12-month intervention.

OBJECTIVE

We quantified treatment response to an intensive neurorehabilitation mobility and fitness program.

METHODS

The 12-month neurorehabilitation program targeted impairments in balance, limb coordination, gait coordination, and functional mobility, for five chronic stroke survivors. We obtained measures of those variables every two months.

RESULTS

We found statistically and clinically significant group improvement in measures of impairment and function. There was high variation across individuals in terms of the timing and the gains exhibited.

CONCLUSIONS

Long-duration neurorehabilitation (12 months) for mobility/fitness produced clinically and/or statistically significant gains in impairment and function. There was unique pattern of change for each individual. Gains exhibited late in the treatment support a 12-month intervention. Some measures for some subjects did not reach a plateau at 12 months, justifying further investigation of a longer program (>12 months) of rehabilitation and/or maintenance care for stroke survivors.

A novel probabilistic generator for large-scale gene association networks

MOTIVATION

Gene expression data provide an opportunity for reverse-engineering gene-gene associations using network inference methods. However, it is difficult to assess the performance of these methods because the true underlying network is unknown in real data. Current benchmarks address this problem by subsampling a known regulatory network to conduct simulations. But the topology of regulatory networks can vary greatly across organisms or tissues, and reference-based generators-such as GeneNetWeaver-are not designed to capture this heterogeneity. This means, for example, benchmark results from the E. coli regulatory network will not carry over to other organisms or tissues. In contrast, probabilistic generators do not require a reference network, and they have the potential to capture a rich distribution of topologies. This makes probabilistic generators an ideal approach for obtaining a robust benchmarking of network inference methods.

RESULTS

We propose a novel probabilistic network generator that (1) provides an alternative to address the inherent limitation of reference-based generators and (2) is able to create realistic gene association networks, and (3) captures the heterogeneity found across gold-standard networks better than existing generators used in practice. Eight organism-specific and 12 human tissue-specific gold-standard association networks are considered. Several measures of global topology are used to determine the similarity of generated networks to the gold-standards. Along with demonstrating the variability of network structure across organisms and tissues, we show that the commonly used "scale-free" model is insufficient for replicating these structures.

AVAILABILITY

This generator is implemented in the R package "SeqNet" and is available on CRAN (https://cran.r-project.org/web/packages/SeqNet/index.html).

The Analysis of Gene Expression Data Incorporating Tumor Purity Information

The tumor microenvironment is composed of tumor cells, stroma cells, immune cells, blood vessels, and other associated non-cancerous cells. Gene expression measurements on tumor samples are an average over cells in the microenvironment. However, research questions often seek answers about tumor cells rather than the surrounding non-tumor tissue. Previous studies have suggested that the tumor purity (TP)-the proportion of tumor cells in a solid tumor sample-has a confounding effect on differential expression (DE) analysis of high vs. low survival groups. We investigate three ways incorporating the TP information in the two statistical methods used for analyzing gene expression data, namely, differential network (DN) analysis and DE analysis. Analysis 1 ignores the TP information completely, Analysis 2 uses a truncated sample by removing the low TP samples, and Analysis 3 uses TP as a covariate in the underlying statistical models. We use three gene expression data sets related to three different cancers from the Cancer Genome Atlas (TCGA) for our investigation. The networks from Analysis 2 have greater amount of differential connectivity in the two networks than that from Analysis 1 in all three cancer datasets. Similarly, Analysis 1 identified more differentially expressed genes than Analysis 2. Results of DN and DE analyses using Analysis 3 were mostly consistent with those of Analysis 1 across three cancers. However, Analysis 3 identified additional cancer-related genes in both DN and DE analyses. Our findings suggest that using TP as a covariate in a linear model is appropriate for DE analysis, but a more robust model is needed for DN analysis. However, because true DN or DE patterns are not known for the empirical datasets, simulated datasets can be used to study the statistical properties of these methods in future studies.

SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data

Gene expression data provide an abundant resource for inferring connections in gene regulatory networks. While methodologies developed for this task have shown success, a challenge remains in comparing the performance among methods. Gold-standard datasets are scarce and limited in use. And while tools for simulating expression data are available, they are not designed to resemble the data obtained from RNA-seq experiments. SeqNet is an R package that provides tools for generating a rich variety of gene network structures and simulating RNA-seq data from them. This produces in silico RNA-seq data for benchmarking and assessing gene network inference methods. The package is available on CRAN and on GitHub at https://github.com/tgrimes/SeqNet.

Medication-related harm and the newspapers - what has been communicated to the public in Ireland: A systematic content analysis

Introduction

Reducing the global prevalence of severe, avoidable medication-related harm (MRH) by 50% by the end of 2022 is the WHO’s third global patient safety challenge [1]. MRH is reported frequently in the academic literature, with increasing age being a key risk factor. The WHO have highlighted the need to improve public health literacy and knowledge about medications. Little is known about the frequency and nature of Irish newspaper reports about MRH. This study sought to address this gap and to examine reporting during the calendar years 2019 and 2009.

Methods

In this mixed-methods study, LexisNexis® [2], an online newspaper archive database, was searched for newspaper articles reporting on MRH, published in the Republic of Ireland during the calendar years 2019 and 2009. The search strategy focussed on “medication” AND “harm” AND “patient”. Quantitative data extraction aimed to describe the frequency (by count of articles) of reporting of MRH and the nature by describing the publishing newspaper titles and the reported details of: drug class(es), demographics (age or life stage, gender) of those experiencing harm and the severity of harm. Qualitatively, a systematic content analysis, using inductive coding is ongoing and will be reported separately. Research ethics committee approval for this study is not required because this is an analysis of material in the public domain.

Results

In total, 7098 newspaper articles were identified through database searching for 2019 (n=3217) and 2009 (n=3881). To date, 54% (3867: n=3217, 45% 2019, n=650, 9% 2009) of these were screened, of which 63 newspaper articles (n=44 2019, n=19 2009) were included and quantitative data were extracted. Within these 63 articles, 71 cases of individual people experiencing MRH were reported (52 in 2019 and 19 in 2009). The newspapers most commonly reporting MRH were Irish Daily Mail (31/63: 27 in 2019 and 4 in 2009) and Irish Times (17/63:9 in 2019 and 8 in 2009). Drug classes most frequently reported as causing MRH were central nervous system drugs (antiepileptics n=10, opioid analgesics n=5, antidepressants n=9, and anxiolytics n=1), cancer chemotherapy (23 cases) and non-steroidal anti-inflammatories (n=3). MRH was reported as being fatal (13 /71:8 in 2019 and 5 in 2009) and non-fatal (58/71), with seven cases (5 in 2019 and 2 in 2009) of permanent harm. Among the 71 individual cases of MRH, the majority were adults aged 18–64 years (n=36), children (n=7), older adults (n=8), foetus (n=3) and newborn (n=1), while the remainder did not report the person’s age.

Conclusion

MRH is frequently reported to the public through Irish newspapers. The study is limited by focus on newsprint media with the exclusion of other forms of digital or social media and restriction to two calendar years in a single country, which likely stifles the generalisability of findings to other contexts. Future work could explore this issue across a wider range of media platforms and examine changes in reporting over time. The study findings may support an agenda to improve the general public's exposure to information and knowledge of MRH and medication safety.

References

1. Donaldson, L.J., et al., Medication without harm: WHO's third global patient safety challenge. 2017. 389(10080): p. 1680–1681.

2. https://advance-lexis-com.elib.tcd.ie/firsttime?crid=d5f713e8-8107-4efd-91cc-1e99c82cdb58&pdmfid=1519360.

Integrating gene regulatory pathways into differential network analysis of gene expression data

The advent of next-generation sequencing has introduced new opportunities in analyzing gene expression data. Research in systems biology has taken advantage of these opportunities by gleaning insights into gene regulatory networks through the analysis of gene association networks. Contrasting networks from different populations can reveal the many different roles genes fill, which can lead to new discoveries in gene function. Pathologies can also arise from aberrations in these gene-gene interactions. Exposing these network irregularities provides a new avenue for understanding and treating diseases. A general framework for integrating known gene regulatory pathways into a differential network analysis between two populations is proposed. The framework importantly allows for any gene-gene association measure to be used, and inference is carried out through permutation testing. A simulation study investigates the performance in identifying differentially connected genes when incorporating known pathways, even if the pathway knowledge is partially inaccurate. Another simulation study compares the general framework with four state-of-the-art methods. Two RNA-seq datasets are analyzed to illustrate the use of this framework in practice. In both examples, the analysis reveals genes and pathways that are known to be biologically significant along with potentially novel findings that may be used to motivate future research.

Predicting survival times for neuroblastoma patients using RNA-seq expression profiles

Background

Neuroblastoma is the most common tumor of early childhood and is notorious for its high variability in clinical presentation. Accurate prognosis has remained a challenge for many patients. In this study, expression profiles from RNA-sequencing are used to predict survival times directly. Several models are investigated using various annotation levels of expression profiles (genes, transcripts, and introns), and an ensemble predictor is proposed as a heuristic for combining these different profiles.

Results

The use of RNA-seq data is shown to improve accuracy in comparison to using clinical data alone for predicting overall survival times. Furthermore, clinically high-risk patients can be subclassified based on their predicted overall survival times. In this effort, the best performing model was the elastic net using both transcripts and introns together. This model separated patients into two groups with 2-year overall survival rates of 0.40±0.11 (n=22) versus 0.80±0.05 (n=68). The ensemble approach gave similar results, with groups 0.42±0.10 (n=25) versus 0.82±0.05 (n=65). This suggests that the ensemble is able to effectively combine the individual RNA-seq datasets.

Conclusions

Using predicted survival times based on RNA-seq data can provide improved prognosis by subclassifying clinically high-risk neuroblastoma patients.

Reviewers

This article was reviewed by Subharup Guha and Isabel Nepomuceno.

Agreement between renal prescribing references and determination of prescribing appropriateness in hospitalized patients with chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is a risk factor for adverse drug events. The clinical significance of discordance between renal prescribing references is unknown.

AIM

We determined the prevalence of potentially inappropriate prescribing (PIP) in CKD, measured agreement between two prescribing references, and assessed potential for harm consequent to PIP.

DESIGN

Single-centre observational study.

METHODS

A random sample of hospitalized patients with CKD were grouped according to baseline CKD stage (3, 4, or 5). Prescriptions requiring caution in CKD were referenced against the Renal Drug Handbook (RDH) and British National Formulary (BNF) to identify PIP (non-compliance with recommendations). Inter-reference agreement was measured using percentage agreement and Kappa coefficient. Potential for harm consequent to PIP was assessed by physicians and pharmacists using a validated scale. One-year mortality was compared between patients with or without PIP during admission.

RESULTS

Among 119 patients (median age 73 years, 50% male), 136 cases of PIP were identified in 78 (65.5%) patients. PIP prevalence, per patient, was 64.7% using the BNF and 28.6% using the RDH (fair agreement, Kappa 0.33, P <  0.001). The majority (63.2%) of PIP cases detected exclusively by the BNF carried minimal or no potential for harm. PIP was not significantly associated with one-year mortality (34.7% vs. 21.1%, P = 0.14).

CONCLUSIONS

PIP was common in hospitalized patients with CKD. Substantial discordance between renal prescribing references was apparent. The development of universally-adopted, evidence-based, prescribing guidelines for CKD might optimize medications safety in this vulnerable group.

Survey of medication documentation at hospital discharge: implications for patient safety and continuity of care

BACKGROUND

Medication discrepancies at the time of hospital discharge are common and can result in error, patient/carer inconvenience or patient harm. Providing accurate medication information to the next care provider is necessary to prevent adverse events.

AIMS

To investigate the quality and consistency of medication details generated for such transfer from an Irish teaching hospital.

METHODS

This was an observational study of 139 cardiology patients admitted over a 3 month period during which a pharmacist prospectively recorded details of medication inconsistencies.

RESULTS

A discrepancy in medication documentation at discharge occurred in 10.8% of medication orders, affecting 65.5% of patients. While patient harm was assessed, it was only felt necessary to contact three (2%) patients. The most common inconsistency was drug omission (20.9%).

CONCLUSIONS

Inaccuracy of medication information at hospital discharge is common and compromises quality of care.

Dynamics of viral and proviral loads of feline immunodeficiency virus within the feline central nervous system during the acute phase following intravenous infection

Animal models of human immunodeficiency virus 1, such as feline immunodeficiency virus (FIV), provide the opportunities to dissect the mechanisms of early interactions of the virus with the central nervous system (CNS). The aims of the present study were to evaluate viral loads within CNS, cerebrospinal fluid (CSF), ocular fluid, and the plasma of cats in the first 23 weeks after intravenous inoculation with FIV(GL8). Proviral loads were also determined within peripheral blood mononuclear cells (PBMCs) and brain tissue. In this acute phase of infection, virus entered the brain in the majority of animals. Virus distribution was initially in a random fashion, with more diffuse brain involvement as infection progressed. Virus in the CSF was predictive of brain parenchymal infection. While the peak of virus production in blood coincided with proliferation within brain, more sustained production appeared to continue in brain tissue. In contrast, proviral loads in the brain decreased to undetectable levels in the presence of a strengthening PBMC load. A final observation in this study was that there was no direct correlation between viral loads in regions of brain or ocular tissue and the presence of histopathology.

The reification of normalcy

Many researchers who investigate the putative effects of violent television on normal children claim there is a lifetime sociopathic effect on many of the children who watch. There may be. But there is a prevailing assumption that because television can produce sociopathic effects in a laboratory, that it does outside the laboratory. In addition, uncritical assumptions of psychological normalcy among most viewers are so prevalent among researchers in this field that any pathological lifetime effect may be exaggerated. The incidence of psychopathology, especially among nonrandom subject samples obtained from public schools, may be higher than investigators suspect, which could lead to overestimates of pernicious effects by television on children. Because pathological children are more vulnerable to commercial television's putative sociopathic effects than are normal children, they may bias study results toward sociopathic attitudes and behaviors, thus misleading researchers into believing that television has a greater sociopathic effect on normal populations than it actually has. Those psychopathologies are reviewed and prospective remedies are suggested for helping those children cope with the possible sociopathic effects of violently oriented television.

Emotionally disturbed children's reactions to violent media segments

This study examined the reaction of children with a diagnosed disruptive behavior disorder (DBD) to violent movie scenes. Children without one of these disorders were tested as well. DBD children ranged in age from 8 to 12 years and were outpatients at The University of Kansas Medical Center's Department of Child Psychiatry. These children were diagnosed by a child psychiatrist as meeting Diagnostic and Statistical Manual of Mental Disorders (4th edition) (American Psychiatric Association 1994) (DSM-IV) diagnostic criteria for having at least one of three emotional disorders: attention-deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD). Results showed that the disordered children differed from the nondisordered children on several dimensions. This suggests that DBD children process the anti-social messages in violent movies differently from children without a psychiatric disorder. An unabated diet of antisocial media could have harmful effects on children with a psychiatric illness.