A reverse translational study of PPAR-α agonist efficacy in human and rodent models relevant to alcohol use disorder.

Alcohol Use Disorder (AUD) is a chronic relapsing disorder affecting an estimated 283 million individuals worldwide, with substantial health and economic consequences. Peroxisome proliferator-activated receptors (PPARs), particularly PPAR-α and PPAR-γ, have shown promise in preclinical studies as potential therapeutic targets for AUD. In this human laboratory study, we aimed to translate preclinical findings on the PPAR-α agonist fenofibrate to a human population with current AUD. We hypothesized that, relative to placebo, fenofibrate at the highest FDA-approved dose of 145 mg/d would attenuate responsiveness to in vivo alcohol cues in the lab and reduce drinking under natural conditions. However, the results did not show significant differences in craving and alcohol consumption between the fenofibrate and placebo groups. Reverse translational studies in rodent models confirmed the lack of fenofibrate effect at human-equivalent doses. These findings suggest that inadequate translation of drug dose from rodents to humans may account for the lack of fenofibrate effects on alcohol craving and consumption in humans with AUD. The results highlight the need for new brain-penetrant PPAR-α agonists to adequately test the therapeutic potential of PPAR-α agonists for AUD, and the importance of reverse translational approaches and selection of human-equivalent doses in drug development.

Epigenetic biomarkers for disease susceptibility and preventative medicine.

The development of molecular biomarkers for disease makes it possible for preventative medicine approaches to be considered. Therefore, therapeutics, treatments, or clinical management can be used to delay or prevent disease development. The problem with genetic mutations as biomarkers is the low frequency with genome-wide association studies (GWASs), generally at best a 1% association of the patients with the disease. In contrast, epigenetic alterations have a high-frequency association of greater than 90%-95% of individuals with pathology in epigenome-wide association studies (EWASs). A wide variety of human diseases have been shown to have epigenetic biomarkers that are disease specific and that detect pathology susceptibility. This review is focused on the epigenetic biomarkers for disease susceptibility, and it distinct from the large literature on epigenetics of disease etiology or progression. The development of efficient epigenetic biomarkers for disease susceptibility will facilitate a paradigm shift from reactionary medicine to preventative medicine.

Could the sperm epigenome become a diagnostic tool for evaluation of the infertile man?

Although male infertility is currently diagnosed when abnormal sperm parameters are found, the poor predictive ability of sperm parameters on natural fecundity and medically assisted reproduction outcome poses the need for improved diagnostic techniques for male infertility. The accumulating evidence about the role played by the sperm epigenome in modulation of the early phases of embryonic development has led researchers to focus on the epigenetic mechanisms within the sperm epigenome to find new molecular markers of male infertility. Indeed, sperm epigenome abnormalities could explain some cases of unexplained male infertility in men showing normal sperm parameters and were found to be associated with poor embryo development in IVF cycles. The present mini-review summarizes the current knowledge about this interesting topic, starting from a description of the epigenetic mechanisms of gene expression regulation (i.e. DNA methylation, histone modifications, and non-coding RNAs' activity). We also discuss possible mechanisms by which environmental factors might cause epigenetic changes in the human germline and affect embryonic development, as well as subsequent generations' phenotypes. Studies demonstrating sperm epigenome abnormalities in men with male infertility are reviewed, with particular emphasis on those with the more severe form of spermatogenic dysfunction. Observations demonstrate that the diagnostic and prognostic efficacy of sperm epigenome evaluation will help facilitate the management of men with male factor infertility.

Identifying unique exposure-specific transgenerational differentially DNA methylated region epimutations in the genome using hybrid deep learning prediction models.

Exposure to environmental toxicants can lead to epimutations in the genome and an increase in differential DNA methylated regions (DMRs) that have been linked to increased susceptibility to various diseases. However, the unique effect of particular toxicants on the genome in terms of leading to unique DMRs for the toxicants has been less studied. One hurdle to such studies is the low number of observed DMRs per toxicants. To address this hurdle, a previously validated hybrid deep-learning cross-exposure prediction model is trained per exposure and used to predict exposure-specific DMRs in the genome. Given these predicted exposure-specific DMRs, a set of unique DMRs per exposure can be identified. Analysis of these unique DMRs through visualization, DNA sequence motif matching, and gene association reveals known and unknown links between individual exposures and their unique effects on the genome. The results indicate the potential ability to define exposure-specific epigenetic markers in the genome and the potential relative impact of different exposures. Therefore, a computational approach to predict exposure-specific transgenerational epimutations was developed, which supported the exposure specificity of ancestral toxicant actions and provided epigenome information on the DMR sites predicted.

Hybrid deep learning approach to improve classification of low-volume high-dimensional data.

BACKGROUND: The performance of machine learning classification methods relies heavily on the choice of features. In many domains, feature generation can be labor-intensive and require domain knowledge, and feature selection methods do not scale well in high-dimensional datasets. Deep learning has shown success in feature generation but requires large datasets to achieve high classification accuracy. Biology domains typically exhibit these challenges with numerous handcrafted features (high-dimensional) and small amounts of training data (low volume). METHOD: A hybrid learning approach is proposed that first trains a deep network on the training data, extracts features from the deep network, and then uses these features to re-express the data for input to a non-deep learning method, which is trained to perform the final classification. RESULTS: The approach is systematically evaluated to determine the best layer of the deep learning network from which to extract features and the threshold on training data volume that prefers this approach. Results from several domains show that this hybrid approach outperforms standalone deep and non-deep learning methods, especially on low-volume, high-dimensional datasets. The diverse collection of datasets further supports the robustness of the approach across different domains. CONCLUSIONS: The hybrid approach combines the strengths of deep and non-deep learning paradigms to achieve high performance on high-dimensional, low volume learning tasks that are typical in biology domains.

Efficacy of Fowlpox Virus Vector Vaccine Expressing VP2 and Chicken Interleukin-18 in the Protection against Infectious Bursal Disease Virus.

In mammals, the role of interleukin-18 (IL-18) in the immune response is to drive inflammatory and, normally therefore, anti-viral responses. IL-18 also shows promise as a vaccine adjuvant in mammals. Chicken IL-18 (chIL-18) has been cloned. The aim of this study was to investigate the potential of chIL-18 to act as a vaccine adjuvant in the context of a live recombinant Fowlpox virus vaccine (fpIBD1) against Infectious bursal disease virus (IBDV). fpIBD1 protects against mortality, but not against damage to the bursa of Fabricius caused by IBDV infection. The Fowlpox virus genome itself contains several candidate immunomodulatory genes, including potential IL-18 binding proteins (IL-18bp). We knocked out (Δ) the potential IL-18bp genes in fpIBD1 and inserted (::) the cDNA encoding chIL-18 into fpIBD1 in the non-essential ORF030, generating five new viral constructs -fpIBD1::chIL-18, fpIBD1ΔORF073, fpIBD1ΔORF073::chIL-18, fpIBD1ΔORF214, and fpIBD1ΔORF214::chIL-18. The subsequent protection from challenge with virulent IBDV, as measured by viral load and bursal damage, given by these altered fpIBD1 strains, was compared to that given by the original fpIBD1. Complete protection was provided following challenge with IBDV in chicken groups vaccinated with either fpIBDIΔ073::IL-18 or fpIBD1Δ214::IL-18, as no bursal damage nor IBDV was detected in the bursae of the birds. The results show that chIL-18 can act as an effective vaccine adjuvant by improving the fpIBD1 vaccine and providing complete protection against IBDV challenge.

Epigenome-wide association study of systemic effects of obesity susceptibility in human twins.

The current study was designed to use an epigenome-wide association approach (EWAS) to identify potential systemic DNA methylation alterations that are associated with obesity using 22 discordant twin pairs. Buccal cells (from a cheek swab) were used as a non-obesity relevant purified marker cell for the epigenetic analysis. Analysis of differential DNA methylation regions (DMRs) was used to identify epigenetic associations with metabolic and dietary measures related to obesity with discordant twins. An edgeR analysis provided a DMR signature with p < 1e-04, but statistical significance was reduced due to low sample size and known multiple origins of obesity. A weighted gene coexpression network analysis (WGCNA) was performed and identified modules (p < 0.005) of epigenetic sites that correlated with different metabolic and dietary measures. The DMR and WGCNA epigenetic sites were near genes (e.g., CIDEC, SPP1, ZFPG9, and POMC) with previously identified obesity associated pathways (e.g., metabolism, cholesterol, and fat digestion). Observations demonstrate the feasibility of identifying systemic epigenetic biomarkers for obesity, which can be further investigated for clinical relevance in future research with larger sample sizes. The availability of a systemic epigenetic biomarker for obesity susceptibility may facilitate preventative medicine and clinical management of the disease early in life.

Analysis of differential DNA methylation regions (DMRs) was used to identify epigenetic associations with metabolic and dietary measures related to obesity with discordant twins.A weighted genome coexpression network analysis (WGCNA) was performed and identified modules of epigenetic sites that correlated with different metabolic and dietary measures.Observations demonstrate the feasibility of identifying systemic epigenetic biomarkers for obesity, which can be further investigated for clinical relevance in future research with larger sample sizes.The availability of a systemic epigenetic biomarker for obesity susceptibility may facilitate preventative medicine and clinical management of the disease early in life.

Creating resistance to avian influenza infection through genome editing of the ANP32 gene family.

Chickens genetically resistant to avian influenza could prevent future outbreaks. In chickens, influenza A virus (IAV) relies on host protein ANP32A. Here we use CRISPR/Cas9 to generate homozygous gene edited (GE) chickens containing two ANP32A amino acid substitutions that prevent viral polymerase interaction. After IAV challenge, 9/10 edited chickens remain uninfected. Challenge with a higher dose, however, led to breakthrough infections. Breakthrough IAV virus contained IAV polymerase gene mutations that conferred adaptation to the edited chicken ANP32A. Unexpectedly, this virus also replicated in chicken embryos edited to remove the entire ANP32A gene and instead co-opted alternative ANP32 protein family members, chicken ANP32B and ANP32E. Additional genome editing for removal of ANP32B and ANP32E eliminated all viral growth in chicken cells. Our data illustrate a first proof of concept step to generate IAV-resistant chickens and show that multiple genetic modifications will be required to curtail viral escape.

Systemic epigenome-wide association study of elk treponeme-associated hoof disease.

Treponeme-associated hoof disease (TAHD) is an emerging disease of elk (Cervus canadensis) in the U.S. Pacific West. Because environmental epigenetics is the primary molecular process that mediates environmental factor impacts on a host organism and disease, the role of epigenetics in TAHD etiology was examined. The current study was designed to examine potential effects of TAHD on systemic epigenetic modifications in infected elk over a range of TAHD lesion severity. Leg tendons that contain predominantly fibroblast connective tissue cells were used to isolate fibroblast cells for epigenetic analysis in unaffected and TAHD-positive male and female Roosevelt and Rocky Mountain elk. Differential DNA methylation regions (DMRs) between the unaffected and TAHD-positive elk were identified for both female and male elk. The presence of TAHD was associated with alteration of the connective tissue cell epigenetics, and DMR associated genes identified. Therefore, the infected elk were found to have a systemic epigenetic alteration that was associated with the disease, despite pathology being generally limited to feet. If the elk germline epigenetics is altered then generational transmission of susceptibility to TAHD may impact subsequent generations through epigenetic inheritance. This first study of epigenetic changes associated with disease in elk suggests that TAHD promotes a systemic effect on the elk epigenetics which could exert health impacts on the elk.

Epigenetic Inheritance and Transgenerational Environmental Justice.

Many chemicals and toxicants are released into our ecosystem and environment every day, which can cause harmful effects on human populations. Agricultural compounds are used in most crop production and have been shown to cause negative health impacts, including effects on reproduction and other pathologies. Although these chemicals can be helpful for pest and weed control, the compounds indirectly impact humans. Several compounds have been banned in the European Union but continue to be used in the United States. Recent work has shown most toxicants affect transgenerational generations more than the directly exposed generations through epigenetic inheritance. While some toxicants do not impact the directly exposed generation, the later generations that are transgenerational or ancestrally exposed suffer health impacts. Due to impacts to future generations, exposure becomes an environmental justice concern. The term "environmental justice" denotes the application of fair strategies when resolving unjust environmental contamination. Fair treatment means that no group should bear a disproportionate share of negative environmental consequences resulting from industrial, municipal, and commercial operations. This article illustrates how research on directly exposed generations is often prioritized over studies on transgenerational generations. However, research on the latter generations suggests the need to take environmental justice concerns seriously moving forward, as future generations could be unduly shouldering harms, while not enjoying benefits of production.

Transgenerational sperm DMRs escape DNA methylation erasure during embryonic development and epigenetic inheritance.

Germline transmission of epigenetic information is a critical component of epigenetic inheritance. Previous studies have suggested that an erasure of DNA methylation is required to develop stem cells in the morula embryo. An exception involves imprinted genes that escape this DNA methylation erasure. Transgenerational differential DNA methylation regions (DMRs) have been speculated to be imprinted-like and escape this erasure. The current study was designed to assess if morula embryos escape the erasure of dichlorodiphenyltrichloroethane-induced transgenerational sperm DMR methylation. Observations demonstrate that the majority (98%) of transgenerational sperm DMR sites retain DNA methylation and are not erased, so appearing similar to imprinted-like sites. Interestingly, observations also demonstrate that the majority of low-density CpG genomic sites had a significant increase in DNA methylation in the morula embryo compared to sperm. This is in contrast to the previously observed DNA methylation erasure of higher-density CpG sites. The general erasure of DNA methylation during embryogenesis appears applicable to high-density DNA methylation sites (e.g. CpG islands) but neither to transgenerational DMR methylation sites nor to low-density CpG deserts, which constitute the vast majority of the genome's DNA methylation sites. The role of epigenetics during embryogenesis appears more dynamic than the simple erasure of DNA methylation.

Predicting Cardiac Arrest in Children with Heart Disease: A Novel Machine Learning Algorithm.

BACKGROUND: Children with congenital and acquired heart disease are at a higher risk of cardiac arrest compared to those without heart disease. Although the monitoring of cardiopulmonary resuscitation quality and extracorporeal resuscitation technologies have advanced, survival after cardiac arrest in this population has not improved. Cardiac arrest prevention, using predictive algorithms with machine learning, has the potential to reduce cardiac arrest rates. However, few studies have evaluated the use of these algorithms in predicting cardiac arrest in children with heart disease. METHODS: We collected demographic, laboratory, and vital sign information from the electronic health records (EHR) of all the patients that were admitted to a single-center pediatric cardiac intensive care unit (CICU), between 2010 and 2019, who had a cardiac arrest during their CICU admission, as well as a comparator group of randomly selected non-cardiac-arrest controls. We compared traditional logistic regression modeling against a novel adaptation of a machine learning algorithm (functional gradient boosting), using time series data to predict the risk of cardiac arrest. RESULTS: A total of 160 unique cardiac arrest events were matched to non-cardiac-arrest time periods. Using 11 different variables (vital signs and laboratory values) from the EHR, our algorithm's peak performance for the prediction of cardiac arrest was at one hour prior to the cardiac arrest (AUROC of 0.85 [0.79,0.90]), a performance that was similar to our previously published multivariable logistic regression model. CONCLUSIONS: Our novel machine learning predictive algorithm, which was developed using retrospective data that were collected from the EHR and predicted cardiac arrest in the children that were admitted to a single-center pediatric cardiac intensive care unit, demonstrated a performance that was similar to that of a traditional logistic regression model. While these results are encouraging, future research, including prospective validations with multicenter data, is warranted prior to the implementation of this algorithm as a real-time clinical decision support tool.

Role of epigenetics in the etiology of hypospadias through penile foreskin DNA methylation alterations.

Abnormal penile foreskin development in hypospadias is the most frequent genital malformation in male children, which has increased dramatically in recent decades. A number of environmental factors have been shown to be associated with hypospadias development. The current study investigated the role of epigenetics in the etiology of hypospadias and compared mild (distal), moderate (mid shaft), and severe (proximal) hypospadias. Penile foreskin samples were collected from hypospadias and non-hypospadias individuals to identify alterations in DNA methylation associated with hypospadias. Dramatic numbers of differential DNA methylation regions (DMRs) were observed in the mild hypospadias, with reduced numbers in moderate and low numbers in severe hypospadias. Atresia (cell loss) of the principal foreskin fibroblast is suspected to be a component of the disease etiology. A genome-wide (> 95%) epigenetic analysis was used and the genomic features of the DMRs identified. The DMR associated genes identified a number of novel hypospadias associated genes and pathways, as well as genes and networks known to be involved in hypospadias etiology. Observations demonstrate altered DNA methylation sites in penile foreskin is a component of hypospadias etiology. In addition, a potential role of environmental epigenetics and epigenetic inheritance in hypospadias disease etiology is suggested.

Preclinical and clinical evidence for suppression of alcohol intake by apremilast.

Treatment options for alcohol use disorders (AUDs) have minimally advanced since 2004, while the annual deaths and economic toll have increased alarmingly. Phosphodiesterase type 4 (PDE4) is associated with alcohol and nicotine dependence. PDE4 inhibitors were identified as a potential AUD treatment using a bioinformatics approach. We prioritized a newer PDE4 inhibitor, apremilast, as ideal for repurposing (i.e., FDA approved for psoriasis, low incidence of adverse events, excellent safety profile) and tested it using multiple animal strains and models, as well as in a human phase IIa study. We found that apremilast reduced binge-like alcohol intake and behavioral measures of alcohol motivation in mouse models of genetic risk for drinking to intoxication. Apremilast also reduced excessive alcohol drinking in models of stress-facilitated drinking and alcohol dependence. Using site-directed drug infusions and electrophysiology, we uncovered that apremilast may act to lessen drinking in mice by increasing neural activity in the nucleus accumbens, a key brain region in the regulation of alcohol intake. Importantly, apremilast (90 mg/d) reduced excessive drinking in non-treatment-seeking individuals with AUD in a double-blind, placebo-controlled study. These results demonstrate that apremilast suppresses excessive alcohol drinking across the spectrum of AUD severity.

The Impact of Transparency and Decision Risk on Human-Automation Teaming Outcomes.

OBJECTIVE: Examine the effects of decision risk and automation transparency on the accuracy and timeliness of operator decisions, automation verification rates, and subjective workload. BACKGROUND: Decision aids typically benefit performance, but can provide incorrect advice due to contextual factors, creating the potential for automation disuse or misuse. Decision aids can reduce an operator's manual problem evaluation, and it can also be strategic for operators to minimize verifying automated advice in order to manage workload. METHOD: Participants assigned the optimal unmanned vehicle to complete missions. A decision aid provided advice but was not always reliable. Two levels of decision aid transparency were manipulated between participants. The risk associated with each decision was manipulated using a financial incentive scheme. Participants could use a calculator to verify automated advice; however, this resulted in a financial penalty. RESULTS: For high- compared with low-risk decisions, participants were more likely to reject incorrect automated advice and were more likely to verify automation and reported higher workload. Increased transparency did not lead to more accurate decisions and did not impact workload but decreased automation verification and eliminated the increased decision time associated with high decision risk. CONCLUSION: Increased automation transparency was beneficial in that it decreased automation verification and decreased decision time. The increased workload and automation verification for high-risk missions is not necessarily problematic given the improved automation correct rejection rate. APPLICATION: The findings have potential application to the design of interfaces to improve human-automation teaming, and for anticipating the impact of decision risk on operator behavior.

The Involvement in Alcoholics Anonymous Scale - Short Form: Factor Structure & Validation.

Background: The aim of this research was to examine the psychometrics of a short form version of the multidimensional Involvement in Alcoholics Anonymous scale (IAA-SF) by assessing the factor structure, internal consistency, and predictive validity. While there are several existing measures of involvement in Alcoholics Anonymous, many are either unidimensional or are limited in their ability to gather variation in the level of involvement in the different dimensions of 12-step programs. Objective: To achieve our aim, we used exploratory and principal axis factor analysis, correlation, and logistic regression with two unique and diverse samples. Longitudinal data were collected from a northern Illinois sample of 110 post-treatment adults, and cross-sectional data were from a random sample of 296 recovery home residents in the United States. Results: Results from the first sample suggested three exploratory factors (Principles Involvement, Social Involvement, and Spiritual Involvement) that were concordant with the proposed conceptualization and were then confirmed in the second sample. A 2nd order factor of global involvement was also found. All subscales demonstrated good to excellent internal consistency and were moderately associated with AA affiliation. Global and social involvement predicted greater odds of abstinence 2 years later, but principles and spiritual involvement did not. Conclusion: Overall results suggest the IAA- SF is a valid and reliable 12-item instrument for assessing involvement in the AA program, and the differential prediction suggests potential utility for a multidimensional approach to 12-step involvement.

A case study approach to understanding the pathway to individualised funded supports under the National Disability Insurance Scheme for community-dwelling individuals with acquired brain injury.

BACKGROUND: The National Disability Insurance Scheme (NDIS) offers opportunity against a historical background of underfunded and fragmented services for people with disability. For people with acquired brain injury (ABI), concerns have been raised about how they access NDIS individualised funded supports. The aim of this research was to explore how community-dwelling individuals with ABI in Queensland navigate the NDIS participant pathway to individualised funded supports. METHODS: This study used a multiple case study design within a policy implementation framework. Twelve people with ABI, nine family members and eight NDIS funded and mainstream service providers participated. Data was collected from relevant NDIS documentation, health records and semi-structured interviews with individuals with ABI, family members, and service providers. RESULTS: The current study highlighted the complexity of navigating the NDIS participant pathway of access, planning, implementation and review for people with ABI, their family and service providers. The NDIS pathway was impacted by the insurance and market based NDIS model itself, time, communication, and the requirement for external supports. Equally, the process was affected by environmental factors, individual person and injury factors as well as service providers, with a range of outcomes evident at the individual, family and system level. CONCLUSIONS: Findings suggest that the NDIS has struggled to make specific allowance for people with ABI and the complexity of their disabilities. Providing people with ABI access to the NDIS Complex Support Needs Pathway may redress many of the difficulties people with ABI experience accessing and using NDIS funded supports.