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Ethics is central to scientific and engineering research and practice, but a key challenge for promoting students' ethical formation involves enhancing faculty members' ability and confidence in embedding positive ethical learning experiences into their curriculums. To this end, this paper explores changes in faculty members' approaches to and perceptions of ethics education following their participation in a multi-year interdisciplinary faculty learning community (FLC). We conducted and thematically analyzed semi-structured interviews with 11 participants following the second year of the FLC. Qualitative themes suggested that, following two years of FLC participation, faculty members (1) were better able to articulate their conceptualizations of ethics; (2) became cognizant of how personal experiences, views, and beliefs informed how they introduced ethics into their curriculum; and (3) developed and lived instructional principles that guided their ethics teaching. Results thus suggested that faculty members benefitted from exploring, discussing, and teaching ethics, which (in turn) enabled them to see new opportunities and become confident in integrating ethics into their courses in meaningful ways that aligned with their scholarly identities. Taken together, these data suggest faculty became agents of change for designing, implementing, and refining ethics-related instructional efforts in STEM. This work can guide others interested in designing faculty learning communities to promote instructional skill development, faculty members' awareness of their ethical values, and their ability and agency to design and integrate ethics learning activities alongside departmental peers in an intentional and continuous manner., (© 2024. The Author(s).)

Multivariate network-based analytic methods such as weighted gene co-expression network analysis are frequently applied to human and animal gene-expression data to estimate the first principal component of a module, or module eigengene (ME). MEs are interpreted as multivariate summaries of correlated gene-expression patterns and network connectivity across genes within a module. As such, they have the potential to elucidate the mechanisms by which molecular genomic variation contributes to individual differences in complex traits. Although increasingly used to test for associations between modules and complex traits, the genetic and environmental etiology of MEs has not been empirically established. It is unclear if, and to what degree, individual differences in blood-derived MEs reflect random variation versus familial aggregation arising from heritable or shared environmental influences. We used biometrical genetic analyses to estimate the contribution of genetic and environmental influences on MEs derived from blood lymphocytes collected on a sample of N = 661 older male twins from the Vietnam Era Twin Study of Aging (VETSA) whose mean age at assessment was 67.7 years (SD = 2.6 years, range = 62-74 years). Of the 26 detected MEs, 14 (56%) had statistically significant additive genetic variation with an average heritability of 44% (SD = 0.08, range = 35%-64%). Despite the relatively small sample size, this demonstration of significant family aggregation including estimates of heritability in 14 of the 26 MEs suggests that blood-based MEs are reliable and merit further exploration in terms of their associations with complex traits and diseases., (© 2024 The Author(s). American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC.)

In the past decade, significant advances have been made in finding genomic risk loci for schizophrenia (SCZ). This, in turn, has enabled the search for SCZ resilience loci that mitigate the impact of SCZ risk genes. Recently, we discovered the first genomic resilience profile for SCZ, completely independent from the established risk loci for SCZ. We posited that these resilience loci protect against SCZ for those having a heighted genomic risk for SCZ. Nevertheless, our understanding of genetic resilience remains limited. It remains unclear whether resilience loci foster protection against adverse states associated with SCZ risk related to clinical, cognitive, and brain-structural phenotypes. To address this knowledge gap, we analyzed data from 487,409 participants from the UK Biobank, and found that resilience loci for SCZ afforded protection against lifetime psychiatric (schizophrenia, bipolar disorder, anxiety, and depression) and non-psychiatric medical disorders (such as asthma, cardiovascular disease, digestive disorders, metabolic disorders, and external causes of morbidity and mortality). Resilience loci also protected against self-harm behaviors, improved fluid intelligence, and larger whole-brain and brain-regional sizes. Overall, this study sheds light on the range of phenotypes that are significantly associated with resilience loci within the general population, revealing distinct patterns separate from those associated with SCZ risk loci. Our findings indicate that resilience loci may offer protection against serious psychiatric and medical outcomes, co-morbidities, and cognitive impairment. Therefore, it is conceivable that resilience loci facilitate adaptive processes linked to improved health and life expectancy.

The Research Domain Criteria (RDoC) initiative was established by the US National Institute of Mental Health as a multilevel, disorder-agnostic framework for analysis of human psychopathology through designated domains and constructs, including the "Positive Valence Systems" domain focused on reward-related behavior. This study investigates the reward valuation subconstruct of "effort" and its association with genetic markers, functional neurobiological pathways, and polygenic risk scores for psychopathology in 1215 children aged 6-12 and their parents (n = 1044). All participants completed the effort expenditure for rewards task (EEfRT), which assesses "effort" according to two quantitative measures: hard-task choice and reward sensitivity. Genetic association analyses were undertaken in MAGMA, utilizing EEfRT outcome variables as genome-wide association studies phenotypes to compute SNP and gene-level associations. Genome-wide association analyses found two distinct genetic loci that were significantly associated with measures of reward sensitivity and a separate genetic locus associated with hard task choice. Gene-set enrichment analysis yielded significant associations between "effort" and multiple gene sets involved in reward processing-related pathways, including dopamine receptor signaling, limbic system and forebrain development, and biological response to cocaine. These results serve to establish "effort" as a relevant construct for understanding reward-related behavior at the genetic level and support the RDoC framework for assessing disorder-agnostic psychopathology., (© 2023 Wiley Periodicals LLC.)

Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever "polygenic resilience score" for SCZ (resilient controls n = 3786; polygenic risk score-matched SCZ cases n = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, p = 4.03 × 10 -5 ) using newly released GWAS data from 23 independent case-control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls n = 2821; polygenic risk score-matched SCZ cases n = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score., (© 2023 Wiley Periodicals LLC.)

Intracortical microelectrode arrays (MEAs) are used for recording neural signals. However, indwelling devices result in chronic neuroinflammation, which leads to decreased recording performance through degradation of the device and surrounding tissue. Coating the MEAs with bioactive molecules is being explored to mitigate neuroinflammation. Such approaches often require an intermediate functionalization step such as (3-aminopropyl)triethoxysilane (APTES), which serves as a linker. However, the standalone effect of this intermediate step has not been previously characterized. Here, we investigated the effect of coating MEAs with APTES by comparing APTES-coated to uncoated controls in vivo and ex vivo . First, we measured water contact angles between silicon uncoated and APTES-coated substrates to verify the hydrophilic characteristics of the APTES coating. Next, we implanted MEAs in the motor cortex (M1) of Sprague-Dawley rats with uncoated or APTES-coated devices. We assessed changes in the electrochemical impedance and neural recording performance over a chronic implantation period of 16 weeks. Additionally, histology and bulk gene expression were analyzed to understand further the reactive tissue changes arising from the coating. Results showed that APTES increased the hydrophilicity of the devices and decreased electrochemical impedance at 1 kHz. APTES coatings proved detrimental to the recording performance, as shown by a constant decay up to 16 weeks postimplantation. Bulk gene analysis showed differential changes in gene expression between groups that were inconclusive with regard to the long-term effect on neuronal tissue. Together, these results suggest that APTES coatings are ultimately detrimental to chronic neural recordings. Furthermore, interpretations of studies using APTES as a functionalization step should consider the potential consequences if the final functionalization step is incomplete.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Engineering ethics is a required aspect of accredited ABET programs, but there is widespread variation in how ethics is taught, to what ends, and how those ends are assessed. This variation makes it challenging to identify practices for teaching ethics to engineers aligned with extant practices in the field. In this study, we revise a recent coding framework by reviewing exemplary engineering ethics programs recognized by the National Academy of Engineering in 2016, or what we refer to as "exemplars." We pursue two primary objectives: (1) To apply and revise a prior coding framework to codify ethics learning objectives, instructional strategies, and assessment strategies in engineering education; and (2) To use the revised coding framework to identify trends in learning objectives, instructional strategies, and assessment strategies of NAE exemplars. We employ systemic review procedures to update the coding framework using 24 of 25 exemplars as a data source. The updated framework includes four primary categories associated with learning objectives, instructional strategies, assessment data collection strategies, and assessment design characteristics. Results indicate that ethical sensitivity or awareness was present in every exemplar as a learning objective, often alongside ethical reasoning-based learning objectives and the formation of professional skills. Exemplars employed numerous instructional strategies in tandem, as we coded eight out of 18 instructional strategies among at least half of the exemplars. Assignments/homework and summative reflections were the most oft-used sources of assessment data. Due to our challenges in coding assessment approaches, we offer practical suggestions for assessing engineering ethics instruction which are based on many of our coding discussions. We hope that this coding framework, the results classifying exemplary features of the NAE programs, and our practical suggestions can guide future instructors as they design, classify, assess, and report their approaches to engineering ethics education., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Interrelations between alcohol use disorder and chronic pain have received increasing empirical attention, and several lines of evidence support the possibility of shared genetic liability. However, research on the genetic contributions to the component processes of these complex and potentially overlapping phenotypes remains scarce. The goal of the present study was to test polygenic risk scores (PRSs) for alcohol consumption and multisite chronic pain as predictors of ad lib drinking behavior during an experimental taste test. PRSs were calculated for 209 pain-free, moderate-to-heavy drinkers (57.9% male; 63.6% White). Among White participants, the alcohol and chronic pain PRSs showed nominally significant ( p s < .05) positive associations with the volume of alcohol consumed and peak blood alcohol concentration (BAC), respectively. However, associations did not survive correction for multiple comparisons. When stratifying results by experimental condition (between-subjects design: no-pain vs. pain), the alcohol PRS was significantly and negatively associated with the volume of alcohol poured, consumed, and peak BAC among Black participants randomized to the no-pain condition (all false discovery rate [FDR] p < .05). Conversely, the chronic pain PRS was significantly and positively associated with study outcomes among White participants in both the no-pain (alcohol consumed; FDR p = .037) and pain conditions (peak BAC; FDR p = .017). These findings lend partial support to the assertion that alcohol consumption in the laboratory is reflective of drinking behavior in naturalistic settings. This was also the first study to use a pain-related PRS to predict alcohol outcomes, which may be indicative of shared etiology between base and target traits. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood-brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947-11,816 genes (false-discovery rate-adjusted p < 0.05), including many transcripts that cannot be predicted significantly by a transcriptome-imputation method such as PrediXcan. BrainGENIE recapitulated measured diagnosis-related gene-expression changes in the brain for autism, bipolar disorder, and schizophrenia better than direct correlations from blood and predictions from PrediXcan. We developed a convenient software toolset for deploying BrainGENIE, and provide recommendations for how best to implement models. BrainGENIE complements and, in some ways, outperforms existing transcriptome-imputation tools, providing biologically meaningful predictions and opening new research avenues., (© 2023. The Author(s).)

The history of Indiana University School of Medicine (IUSM) dates to 1871, when Indiana Medical College entered into an affiliation with Indiana University in Bloomington to offer medical education. In 1971, the Indiana General Assembly passed a bill to create and fund a distributed model for medical education for which IUSM was responsible, an innovative approach to implementing a statewide medical education program. IUSM became one of the first U.S. medical schools to implement what is today known as a regional medical campus model. This regional medical campus system has permitted IUSM to expand enrollment based on national and local concerns about physician shortages, increase access to care locally, support expansion of graduate medical education, and provide opportunities for research and scholarship by faculty and students statewide. This effort was made possible by partnerships with other universities and health care systems across the state and the support of local community and state leaders. The model is a forward-thinking and cost-effective way to educate physicians for service in the state of Indiana and is applicable to others. This article highlights milestones in IUSM's 50-year history of regional medical education, describes the development of the regional medical campus model, recognizes significant achievements over the years, shares lessons learned, and discusses considerations for the future of medical education., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Association of American Medical Colleges.)

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Large-scale brain imaging studies by the ENIGMA Consortium identified structural changes associated with attention-deficit/hyperactivity disorder (ADHD). It is not clear why some brain regions are impaired and others spared by the etiological risks for ADHD. We hypothesized that spatial variation in brain cell organization and/or pathway expression levels contribute to selective brain region vulnerability (SBRV) in ADHD. In this study, we used the largest available collection of magnetic resonance imaging (MRI) results from the ADHD ENIGMA Consortium (subcortical MRI n = 3242; cortical MRI n = 4180) along with high-resolution postmortem brain microarray data from Allen Brain Atlas (donors n = 6) from 22 brain regions to investigate our SBRV hypothesis. We performed deconvolution of the bulk transcriptomic data to determine abundances of neuronal and nonneuronal cells in the brain. We assessed the relationships between gene-set expression levels, cell abundance, and standardized effect sizes representing regional changes in brain sizes in cases of ADHD. Our analysis yielded significant correlations between apoptosis, autophagy, and neurodevelopment genes with smaller brain sizes in ADHD, along with associations to regional abundances of astrocytes and oligodendrocytes. The lack of enrichment of common genetic risk variants for ADHD within implicated gene sets suggests an environmental etiology to these differences. This work provides novel mechanistic clues about SBRV in ADHD., (© 2020. The Author(s), under exclusive licence to Springer Nature Limited.)

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures., (© 2021. The Author(s).)

Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531-538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known "polygenic resilience score" that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.

Objective: Developmental theory posits interacting individual and contextual factors that contribute to alcohol use across adolescence. Despite the well-documented salience of peer environmental influences on adolescent drinking, it is not known whether peer environments moderate polygenic risks for trajectories of alcohol use. The current theoretically based investigation aimed to test developmental gene-environment interaction (G×E) effects across adolescence., Method: Latent growth curve models tested interactive associations of polygenic risk scores and adolescents' perceived friend drinking and disruptive behavior with adolescents' initial level of alcohol use frequency at age 16 years old and change in alcohol frequency from ages 16 to 20. The sample comprised 8,941 White adolescents (49% female) from Great Britain within the Avon Longitudinal Study of Parents and Children (ALSPAC)., Results: Greater polygenic risk was associated with more frequent initial drinking as well as escalations in drinking frequency over the subsequent 5 years in latent growth curve models. Contrary to study hypotheses, no significant G×E effects were identified after controlling for confounding main and interaction effects., Conclusions: Adolescents at heightened genetic risk may accelerate their alcohol use across adolescence, although not significantly more so in the presence of these alcohol-promoting peer environments. Future well-powered, theoretically driven replication efforts are needed to examine generalizability of these findings across diverse samples.

The U.S. National Institute of Mental Health (NIMH) introduced the research domain criteria (RDoC) initiative to promote the integration of information across multiple units of analysis (i.e., brain circuits, physiology, behavior, self-reports) to better understand the basic dimensions of behavior and cognitive functioning underlying normal and abnormal mental conditions. Along those lines, this study examined the association between peripheral blood gene expression levels and emotional and behavioral problems in school-age children. Children were chosen from two age- and sex-matched groups: those with or without parental reports of any prior or current psychiatric diagnosis. RNA-sequencing was performed on whole blood from 96 probands aged 6-12 years who were medication-free at the time of assessment. Module eigengenes were derived using weighted gene co-expression network analysis (WGCNA). Associations were tested between module eigengene expression levels and eight syndrome scales from parent ratings on the Child Behavior Checklist (CBCL). Nine out of the 36 modules were significantly associated with at least one syndrome scale measured by the CBCL (i.e., aggression, social problems, attention problems, and/or thought problems) after accounting for covariates and correcting for multiple testing. Our study demonstrates that variation in peripheral blood gene expression relates to emotional and behavioral profiles in children. If replicated and validated, our results may help in identifying problem or at-risk behavior in pediatric populations, and in elucidating the biological pathways that modulate complex human behavior.

Ethical becoming represents a novel framework for teaching engineering ethics. This framework insists on the complementarity of pragmatism, care, and virtue. The dispositional nature of the self is a central concern, as are relational considerations. However, unlike previous conceptual work, this paper introduces additional lenses for exploring ethical relationality by focusing on indebtedness, harmony, potency, and reflective thought. This paper first reviews relevant contributions in the engineering ethics literature. Then, the relational process ontology of Alfred North Whitehead is described and identified as the foundation of the ethical becoming concept. Following this, ethical becoming is imagined as comprising five components: relationality and indebtedness, harmony and potency (i.e., beauty), care, freedom and reflective thought, and ethical inquiry. Each component will be unpacked and knit together to argue that (1) becoming in all its forms is relational and, therefore, whatever becomes is indebted to all to which it relates; (2) one's ethical engagement must be directed toward the creation of harmony and potency; (3) care practices are necessary to ensure that multiplicity is valued and safeguarded in the meeting of needs; (4) the capacity for reflective thought is necessary to fashion one's self and others in the direction of harmony, potency, and care; and (5) ethical thought and action must operate through a cycle of ethical inquiry. This paper will close with a brief exploration of how ethical becoming could be utilized in engineering education contexts.

We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called "major psychosis", including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called "polytranscript risk scoring" that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to declare., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Human genome-wide association studies (GWAS), transcriptome analyses of animal models, and candidate gene studies have advanced our understanding of the genetic architecture of aggressive behaviors. However, each of these methods presents unique limitations. To generate a more confident and comprehensive view of the complex genetics underlying aggression, we undertook an integrated, cross-species approach. We focused on human and rodent models to derive eight gene lists from three main categories of genetic evidence: two sets of genes identified in GWAS studies, four sets implicated by transcriptome-wide studies of rodent models, and two sets of genes with causal evidence from online Mendelian inheritance in man (OMIM) and knockout (KO) mice reports. These gene sets were evaluated for overlap and pathway enrichment to extract their similarities and differences. We identified enriched common pathways such as the G-protein coupled receptor (GPCR) signaling pathway, axon guidance, reelin signaling in neurons, and ERK/MAPK signaling. Also, individual genes were ranked based on their cumulative weights to quantify their importance as risk factors for aggressive behavior, which resulted in 40 top-ranked and highly interconnected genes. The results of our cross-species and integrated approach provide insights into the genetic etiology of aggression.

Academic healthcare programs are incorporating interprofessional education (IPE) into students' learning experiences in order to prepare students for optimal clinical practice. This paper describes a simulation-based learning experience (SBLE) designed to encourage students (n = 130) from six healthcare professions to learn more about interprofessional communication, roles and responsibilities of the healthcare team, and knowledge of interprofessional collaborative practice. Data analysis showed statistically significant differences in participants' perceptions of roles/responsibilities for collaborative practice (p = 0.001) and the patient outcomes from collaborative practice (p = 0.002). Additionally, participants identified the importance of holistic, patient-centered care, a greater understanding of the roles and responsibilities of healthcare team members, and a greater desire to participate in IPE activities. Utilizing SBLE with students in athletic training, nursing, occupational therapy, physical therapy, social work, and psychology led to positive perceptions of IPE and collaborative practice.

C/EBPα plays a key role in specifying myeloid lineage development. HoxA9 is expressed in myeloid progenitors, with its level diminishing during myeloid maturation, and HOXA9 is over-expressed in a majority of acute myeloid leukemia cases, including those expressing NUP98-HOXD13. The objective of this study was to determine whether HoxA9 directly represses Cebpa gene expression. We find 4-fold increased HoxA9 and 5-fold reduced Cebpa in marrow common myeloid and LSK progenitors from Vav-NUP98-HOXD13 transgenic mice. Conversely, HoxA9 decreases 5-fold while Cebpa increases during granulocytic differentiation of 32Dcl3 myeloid cells. Activation of exogenous HoxA9-ER in 32Dcl3 cells reduces Cebpa mRNA even in the presence of cycloheximide, suggesting direct repression. Cebpa transcription in murine myeloid cells is regulated by a hematopoietic-specific +37 kb enhancer and by a more widely active +8 kb enhancer. ChIP-Seq analysis of primary myeloid progenitor cells expressing exogenous HoxA9 or HoxA9-ER demonstrates that HoxA9 localizes to both the +8 kb and +37 kb Cebpa enhancers. Gel shift analysis demonstrates HoxA9 binding to three consensus sites in the +8 kb enhancer, but no affinity for the single near-consensus site present in the +37 kb enhancer. Activity of a Cebpa +8 kb enhancer/promoter-luciferase reporter in 32Dcl3 or MOLM14 myeloid cells is increased ~2-fold by mutation of its three HOXA9-binding sites, suggesting that endogenous HoxA9 represses +8 kb Cebpa enhancer activity. In contrast, mutation of five C/EBPα-binding sites in the +8 kb enhancer reduces activity 3-fold. Finally, expression of a +37 kb enhancer/promoter-hCD4 transgene reporter is reduced ~2-fold in marrow common myeloid progenitors when the Vav-NUP98-HOXD13 transgene is introduced. Overall, these data support the conclusion that HoxA9 represses Cebpa expression, at least in part via inhibition of its +8 kb enhancer, potentially allowing normal myeloid progenitors to maintain immaturity and contributing to the pathogenesis of acute myeloid leukemia associated with increased HOXA9., Competing Interests: The authors have declared that no competing interests exist.

Aberrant expression of HOXA9 is a prominent feature of acute leukemia driven by diverse oncogenes. Here we show that HOXA9 overexpression in myeloid and B progenitor cells leads to significant enhancer reorganizations with prominent emergence of leukemia-specific de novo enhancers. Alterations in the enhancer landscape lead to activation of an ectopic embryonic gene program. We show that HOXA9 functions as a pioneer factor at de novo enhancers and recruits CEBPα and the MLL3/MLL4 complex. Genetic deletion of MLL3/MLL4 blocks histone H3K4 methylation at de novo enhancers and inhibits HOXA9/MEIS1-mediated leukemogenesis in vivo. These results suggest that therapeutic targeting of HOXA9-dependent enhancer reorganization can be an effective therapeutic strategy in acute leukemia with HOXA9 overexpression., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies to determine if commonly varying single nucleotide polymorphisms are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohn's disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations among the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study., (© 2018 Wiley Periodicals, Inc.)

Sub-cortical volumetric differences were associated with attention-deficit/hyperactivity disorder (ADHD) in a recent multi-site, mega-analysis of 1713 ADHD persons and 1529 controls. As there was a wide range of effect sizes among the sub-cortical volumes, it is possible that selective neuronal vulnerability has a role in these volumetric losses. To address this possibility, we used data from Allen Brain Atlas to investigate variability in gene expression profiles between subcortical regions of typically developing brains. We tested the hypothesis that the expression of genes in a set of curated ADHD candidate genes and five a priori selected, biological pathways would be associated with the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) findings. Across the subcortical regions studied by ENIGMA, gene expression profiles for three pathways were significantly correlated with ADHD-associated volumetric reductions: apoptosis, oxidative stress and autophagy. These correlations were strong and significant for children with ADHD, but not for adults. Although preliminary, these data suggest that variability of structural brain anomalies in ADHD can be explained, in part, by the differential vulnerability of these regions to mechanisms mediating apoptosis, oxidative stress and autophagy.

Promoting the ethical formation of engineering students through the cultivation of their discipline-specific knowledge, sensitivity, imagination, and reasoning skills has become a goal for many engineering education programs throughout the United States. However, there is neither a consensus throughout the engineering education community regarding which strategies are most effective towards which ends, nor which ends are most important. This study provides an overview of engineering ethics interventions within the U.S. through the systematic analysis of articles that featured ethical interventions in engineering, published in select peer-reviewed journals, and published between 2000 and 2015. As a core criterion, each journal article reviewed must have provided an overview of the course as well as how the authors evaluated course-learning goals. In sum, 26 articles were analyzed with a coding scheme that included 56 binary items. The results indicate that the most common methods for integrating ethics into engineering involved exposing students to codes/standards, utilizing case studies, and discussion activities. Nearly half of the articles had students engage with ethical heuristics or philosophical ethics. Following the presentation of the results, this study describes in detail four articles to highlight less common but intriguing pedagogical methods and evaluation techniques. The findings indicate that there is limited empirical work on ethics education within engineering across the United States. Furthermore, due to the large variation in goals, approaches, and evaluation methods described across interventions, this study does not detail "best" practices for integrating ethics into engineering. The science and engineering education community should continue exploring the relative merits of different approaches to ethics education in engineering.

Background: Two single-nucleotide polymorphisms (SNPs) (rs4281084 and rs12155594) within the neuregulin-1 (NRG1) gene have been associated with psychosis transition. However, the neurobiological changes associated with these SNPs remain unclear. We aimed to determine what relationship these two SNPs have on lateral ventricular volume and white matter integrity, as abnormalities in these brain structures are some of the most consistent in schizophrenia., Methods: Structural (n = 370) and diffusion (n = 465) magnetic resonance imaging data were obtained from affected and unaffected individuals predominantly of European descent. The SNPs rs4281084, rs12155594, and their combined allelic load were examined for their effects on lateral ventricular volume, fractional anisotropy (FA) as well as axial (AD) and radial (RD) diffusivity. Additional exploratory analyses assessed NRG1 effects on gray matter volume, cortical thickness, and surface area throughout the brain., Results: Individuals with a schizophrenia age of onset ⩽25 and a combined allelic load ⩾3 NRG1 risk alleles had significantly larger right (up to 50%, p adj = 0.01) and left (up to 45%, p adj = 0.05) lateral ventricle volumes compared with those with allelic loads of less than three. Furthermore, carriers of three or more risk alleles, regardless of age of onset and case status, had significantly reduced FA and elevated RD but stable AD in the frontal cortex compared with those carrying fewer than three risk alleles., Conclusions: Our findings build on a growing body of research supporting the functional importance of genetic variation within the NRG1 gene and complement previous findings implicating the rs4281084 and rs12155594 SNPs as markers for psychosis transition.

Transcriptome-wide screens of peripheral blood during the onset and development of posttraumatic stress disorder (PTSD) indicate widespread immune dysregulation. However, little is known as to whether biological sex and the type of traumatic event influence shared or distinct biological pathways in PTSD. We performed a combined analysis of five independent PTSD blood transcriptome studies covering seven types of trauma in 229 PTSD and 311 comparison individuals to synthesize the extant data. Analyses by trauma type revealed a clear pattern of PTSD gene expression signatures distinguishing interpersonal (IP)-related traumas from combat-related traumas. Co-expression network analyses integrated all data and identified distinct gene expression perturbations across sex and modes of trauma in PTSD, including one wound-healing module downregulated in men exposed to combat traumas, one IL-12-mediated signaling module upregulated in men exposed to IP-related traumas, and two modules associated with lipid metabolism and mitogen-activated protein kinase activity upregulated in women exposed to IP-related traumas. Remarkably, a high degree of sharing of transcriptional dysregulation across sex and modes of trauma in PTSD was also observed converging on common signaling cascades, including cytokine, innate immune, and type I interferon pathways. Collectively, these findings provide a broad view of immune dysregulation in PTSD and demonstrate inflammatory pathways of molecular convergence and specificity, which may inform mechanisms and diagnostic biomarkers for the disorder.

Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Genome-wide expression studies of samples derived from individuals with autism spectrum disorder (ASD) and their unaffected siblings have been widely used to shed light on transcriptomic differences associated with this condition. Females have historically been under-represented in ASD genomic studies. Emerging evidence from studies of structural genetic variants and peripheral biomarkers suggest that sex-differences may exist in the biological correlates of ASD. Relatively few studies have explicitly examined whether sex-differences exist in the transcriptomic signature of ASD. The present study quantified genome-wide expression values by performing RNA sequencing on transformed lymphoblastoid cell lines and identified transcripts differentially expressed between same-sex, proximal-aged sibling pairs. We found that performing separate analyses for each sex improved our ability to detect ASD-related transcriptomic differences; we observed a larger number of dysregulated genes within our smaller set of female samples (n = 12 sibling pairs), as compared with the set of male samples (n = 24 sibling pairs), with small, but statistically significant overlap between the sexes. Permutation-based gene-set analyses and weighted gene co-expression network analyses also supported the idea that the transcriptomic signature of ASD may differ between males and females. We discuss our findings in the context of the relevant literature, underscoring the need for future ASD studies to explicitly account for differences between the sexes. Autism Res 2017, 10: 439-455. © 2016 International Society for Autism Research, Wiley Periodicals, Inc., (© 2016 International Society for Autism Research, Wiley Periodicals, Inc.)