Specification curve analysis to identify heterogeneity in risk factors for dementia: findings from the UK Biobank.

BACKGROUND: In 2020, the Lancet Commission identified 12 risk factors as priorities for prevention of dementia, and other studies identified APOE e4/e4 genotype and family history of Alzheimer's disease strongly associated with dementia outcomes; however, it is unclear how robust these relationships are across dementia subtypes and analytic scenarios. Specification curve analysis (SCA) is a new tool to probe how plausible analytical scenarios influence outcomes. METHODS: We evaluated the heterogeneity of odds ratios for 12 risk factors reported from the Lancet 2020 report and two additional strong associated non-modifiable factors (APOE e4/e4 genotype and family history of Alzheimer's disease) with dementia outcomes across 450,707 UK Biobank participants using SCA with 5357 specifications across dementia subtypes (outcomes) and analytic models (e.g., standard demographic covariates such as age or sex and/or 14 correlated risk factors). RESULTS: SCA revealed variable dementia risks by subtype and age, with associations for TBI and APOE e4/e4 robust to model specification; in contrast, diabetes showed fluctuating links with dementia subtypes. We found that unattributed dementia participants had similar risk factor profiles to participants with defined subtypes. CONCLUSIONS: We observed heterogeneity in the risk of dementia, and estimates of risk were influenced by the inclusion of a combination of other modifiable risk factors; non-modifiable demographic factors had a minimal role in analytic heterogeneity. Future studies should report multiple plausible analytic scenarios to test the robustness of their association. Considering these combinations of risk factors could be advantageous for the clinical development and evaluation of novel screening models for different types of dementia.

Dose mediates the protracted effects of adolescent THC exposure on reward and stress reactivity in males relevant to perturbation of the basolateral amygdala transcriptome.

Despite the belief that cannabis is relatively harmless, exposure during adolescence is associated with increased risk of developing several psychopathologies in adulthood. In addition to the high levels of use amongst teenagers, the potency of ∆-9-tetrahydrocannabinol (THC) has increased more than fourfold compared to even twenty years ago, and it is unclear whether potency influences the presentation of THC-induced behaviors. Expanded knowledge about the impact of adolescent THC exposure, especially high dose, is important to delineating neural networks and molecular mechanisms underlying psychiatric risk. Here, we observed that repeated exposure to low (1.5 mg/kg) and high (5 mg/kg) doses of THC during adolescence in male rats produced divergent effects on behavior in adulthood. Whereas low dose rats showed greater sensitivity to reward devaluation and also self-administered more heroin, high dose animals were significantly more reactive to social isolation stress. RNA sequencing of the basolateral amygdala, a region linked to reward processing and stress, revealed significant perturbations in transcripts and gene networks related to synaptic plasticity and HPA axis that were distinct to THC dose as well as stress. In silico single-cell deconvolution of the RNAseq data revealed a significant reduction of astrocyte-specific genes related to glutamate regulation in stressed high dose animals, a result paired anatomically with greater astrocyte-to-neuron ratios and hypotrophic astrocytes. These findings emphasize the importance of dose and behavioral state on the presentation of THC-related behavioral phenotypes in adulthood and dysregulation of astrocytes as an interface for the protracted effects of high dose THC and subsequent stress sensitivity.

Long-Term Outcomes of Adolescent THC Exposure on Translational Cognitive Measures in Adulthood in an Animal Model and Computational Assessment of Human Data.

Importance: Although perceived as relatively harmless and nonaddictive, adolescent cannabis use significantly increases the likelihood of developing cannabis use disorder in adulthood, especially for high-potency cannabis. Risky decision-making is associated with chronic cannabis use, but given confounds of human studies, it remains unclear whether adolescent cannabis exposure and Δ9-tetrahydrocannabinol (THC) potency specifically predicts risky decision-making or influences cognitive response to the drug later in life. Objective: To leverage a human data set of cannabis users and a rat model to evaluate the long-term outcomes of adolescent THC exposure on adult decision-making and impulse control. Design, Setting, and Participants: This translational rat study tested the link between adolescent THC exposure and adulthood decision-making. A reanalysis of a previously published dataset of human chronic cannabis users was conducted to evaluate decision-making phenotypes. Computational modeling assessed the human and animal results in a single framework. Data were collected from 2017 to 2020 and analyzed from 2020 to 2022. Main Outcomes and Measures: Decision-making was measured by the Iowa Gambling Task (IGT) and Rat Gambling Task (rGT). Impulse control was assessed in the rat model. Computational modeling was used to determine reward and punishment learning rates and learning strategy used by cannabis users and THC-exposed rats. Cell-specific molecular measures were conducted in the prefrontal cortex and amygdala. Results: Of 37 participants, 24 (65%) were male, and the mean (SD) age was 33.0 (8.3) years. Chronic cannabis users (n = 22; mean [SE] IGT score, -5.182 [1.262]) showed disadvantageous decision-making compared with controls (n = 15; mean [SE] IGT score, 7.133 [2.687]; Cohen d = 1.436). Risky choice was associated with increased reward learning (mean [SE] IGT score: cannabis user, 0.170 [0.018]; control, 0.046 [0.008]; Cohen d = 1.895) and a strategy favoring exploration vs long-term gains (mean [SE] IGT score: cannabis user, 0.088 [0.012]; control, 0.020 [0.002]; Cohen d = 2.218). Rats exposed to high-dose THC but not low-dose THC during adolescence also showed increased risky decision-making (mean [SE] rGT score: vehicle, 46.17 [7.02]; low-dose THC, 69.45 [6.01]; high-dose THC, 21.97 [11.98]; Cohen d = 0.433) and elevated reward learning rates (mean [SE] rGT score: vehicle, 0.17 [0.01]; low-dose THC, 0.10 [0.01]; high-dose THC, 0.24 [0.06]; Cohen d = 1.541) during task acquisition. These animals were also uniquely susceptible to increased cognitive impairments after reexposure to THC in adulthood, which was correlated with even greater reward learning (r = -0.525; P < .001) and a shift in strategy (r = 0.502; P < .001), similar to results seen in human cannabis users. Molecular studies revealed that adolescent THC dose differentially affected cannabinoid-1 receptor messenger RNA expression in the prelimbic cortex and basolateral amygdala in a layer- and cell-specific manner. Further, astrocyte glial fibrillary acidic protein messenger RNA expression associated with cognitive deficits apparent with adult THC reexposure. Conclusions and Relevance: In this translational study, high-dose adolescent THC exposure was associated with cognitive vulnerability in adulthood, especially with THC re-exposure. These data also suggest a link between astrocytes and cognition that altogether provides important insights regarding the neurobiological genesis of risky cannabis use that may help promote prevention and treatment efforts.

Questionable Research Practices, Low Statistical Power, and Other Obstacles to Replicability: Why Preclinical Neuroscience Research Would Benefit from Registered Reports.

Replicability, the degree to which a previous scientific finding can be repeated in a distinct set of data, has been considered an integral component of institutionalized scientific practice since its inception several hundred years ago. In the past decade, large-scale replication studies have demonstrated that replicability is far from favorable, across multiple scientific fields. Here, I evaluate this literature and describe contributing factors including the prevalence of questionable research practices (QRPs), misunderstanding of p-values, and low statistical power. I subsequently discuss how these issues manifest specifically in preclinical neuroscience research. I conclude that these problems are multifaceted and difficult to solve, relying on the actions of early and late career researchers, funding sources, academic publishers, and others. I assert that any viable solution to the problem of substandard replicability must include changing academic incentives, with adoption of registered reports being the most immediately impactful and pragmatic strategy. For animal research in particular, comprehensive reporting guidelines that document potential sources of sensitivity for experimental outcomes is an essential addition.

Prenatal Δ9-Tetrahydrocannabinol Exposure in Males Leads to Motivational Disturbances Related to Striatal Epigenetic Dysregulation.

BACKGROUND: Cannabis remains one of the most widely abused drugs during pregnancy. In utero exposure to its principal psychoactive component, Δ9-tetrahydrocannabinol (THC), can result in long-term neuropsychiatric risk for the progeny. This study investigated epigenetic signatures underlying these enduring consequences. METHODS: Rat dams were exposed daily to THC (0.15 mg/kg) during pregnancy, and adult male offspring were examined for reward and depressive-like behavioral endophenotypes. Using unbiased sequencing approaches, we explored transcriptional and epigenetic profiles in the nucleus accumbens (NAc), a brain area central to reward and emotional processing. An in vitro CRISPR (clustered regularly interspaced short palindromic repeats) activation model coupled with RNA sequencing was also applied to study specific consequences of epigenetic dysregulation, and altered molecular signatures were compared with human major depressive disorder transcriptome datasets. RESULTS: Prenatal THC exposure induced increased motivation for food, heightened learned helplessness and anhedonia, and altered stress sensitivity. We identified a robust increase specific to males in the expression of Kmt2a (histone-lysine N-methyltransferase 2A) that targets H3K4 (lysine 4 on histone H3) in cellular chromatin. Normalizing Kmt2a in the NAc rescued the motivational phenotype of prenatally THC-exposed animals. Comparison of RNA- and H3K4me3-sequencing datasets from the NAc of rat offspring with the in vitro model of Kmt2a upregulation revealed overlapping, significant disturbances in pathways that mediate synaptic plasticity. Similar transcriptional alterations were detected in human major depressive disorder. CONCLUSIONS: These studies provide direct evidence for the persistent effects of prenatal cannabis exposure on transcriptional and epigenetic deviations in the NAc via Kmt2a dysregulation and associated psychiatric vulnerability.

Synaptic Zn2+ potentiates the effects of cocaine on striatal dopamine neurotransmission and behavior.

Cocaine binds to the dopamine (DA) transporter (DAT) to regulate cocaine reward and seeking behavior. Zinc (Zn2+) also binds to the DAT, but the in vivo relevance of this interaction is unknown. We found that Zn2+ concentrations in postmortem brain (caudate) tissue from humans who died of cocaine overdose were significantly lower than in control subjects. Moreover, the level of striatal Zn2+ content in these subjects negatively correlated with plasma levels of benzoylecgonine, a cocaine metabolite indicative of recent use. In mice, repeated cocaine exposure increased synaptic Zn2+ concentrations in the caudate putamen (CPu) and nucleus accumbens (NAc). Cocaine-induced increases in Zn2+ were dependent on the Zn2+ transporter 3 (ZnT3), a neuronal Zn2+ transporter localized to synaptic vesicle membranes, as ZnT3 knockout (KO) mice were insensitive to cocaine-induced increases in striatal Zn2+. ZnT3 KO mice showed significantly lower electrically evoked DA release and greater DA clearance when exposed to cocaine compared to controls. ZnT3 KO mice also displayed significant reductions in cocaine locomotor sensitization, conditioned place preference (CPP), self-administration, and reinstatement compared to control mice and were insensitive to cocaine-induced increases in striatal DAT binding. Finally, dietary Zn2+ deficiency in mice resulted in decreased striatal Zn2+ content, cocaine locomotor sensitization, CPP, and striatal DAT binding. These results indicate that cocaine increases synaptic Zn2+ release and turnover/metabolism in the striatum, and that synaptically released Zn2+ potentiates the effects of cocaine on striatal DA neurotransmission and behavior and is required for cocaine-primed reinstatement. In sum, these findings reveal new insights into cocaine's pharmacological mechanism of action and suggest that Zn2+ may serve as an environmentally derived regulator of DA neurotransmission, cocaine pharmacodynamics, and vulnerability to cocaine use disorders.

SnapShot: Neurobiology of opioid use disorder.

The use of opioid drugs and related overdose deaths, which rose to epidemic proportions over the past decade, have been exacerbated by the COVID pandemic, a time of great uncertainty and isolation. Much is known about opioid pharmacology and related neural circuits that, combined with novel emerging neurobiological insights, can help guide new treatment strategies. To view this SnapShot, open or download the PDF.

bbeaR: an R package and framework for epitope-specific antibody profiling.

SUMMARY: Analysis of epitope-specific antibody repertoires has provided novel insights into the pathogenesis of inflammatory disorders, especially allergies. A novel multiplex immunoassay, termed Bead-Based Epitope Assay (BBEA), was developed to quantify levels of epitope-specific immunoglobulins, including IgE, IgG, IgA and IgD isotypes. bbeaR is an open-source R package, developed for the BBEA, provides a framework to import, process and normalize .csv data files exported from the Luminex reader, evaluate various quality control metrics, analyze differential epitope-binding antibodies with linear modeling, visualize results and map epitopes' amino acid sequences to their respective primary protein structures. bbeaR enables streamlined and reproducible analysis of epitope-specific antibody profiles. AVAILABILITY AND IMPLEMENTATION: bbeaR is open-source and freely available from GitHub as an R package: https://github.com/msuprun/bbeaR; vignettes included. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Striatal Rgs4 regulates feeding and susceptibility to diet-induced obesity.

Consumption of high fat, high sugar (western) diets is a major contributor to the current high levels of obesity. Here, we used a multidisciplinary approach to gain insight into the molecular mechanisms underlying susceptibility to diet-induced obesity (DIO). Using positron emission tomography (PET), we identified the dorsal striatum as the brain area most altered in DIO-susceptible rats and molecular studies within this region highlighted regulator of G-protein signaling 4 (Rgs4) within laser-capture micro-dissected striatonigral (SN) and striatopallidal (SP) medium spiny neurons (MSNs) as playing a key role. Rgs4 is a GTPase accelerating enzyme implicated in plasticity mechanisms of SP MSNs, which are known to regulate feeding and disturbances of which are associated with obesity. Compared to DIO-resistant rats, DIO-susceptible rats exhibited increased striatal Rgs4 with mRNA expression levels enriched in SP MSNs. siRNA-mediated knockdown of striatal Rgs4 in DIO-susceptible rats decreased food intake to levels comparable to DIO-resistant animals. Finally, we demonstrated that the human Rgs4 gene locus is associated with increased body weight and obesity susceptibility phenotypes, and that overweight humans exhibit increased striatal Rgs4 protein. Our findings highlight a novel role for involvement of Rgs4 in SP MSNs in feeding and DIO-susceptibility.

Predicting opioid dependence from electronic health records with machine learning.

BACKGROUND: The opioid epidemic in the United States is averaging over 100 deaths per day due to overdose. The effectiveness of opioids as pain treatments, and the drug-seeking behavior of opioid addicts, leads physicians in the United States to issue over 200 million opioid prescriptions every year. To better understand the biomedical profile of opioid-dependent patients, we analyzed information from electronic health records (EHR) including lab tests, vital signs, medical procedures, prescriptions, and other data from millions of patients to predict opioid substance dependence. RESULTS: We trained a machine learning model to classify patients by likelihood of having a diagnosis of substance dependence using EHR data from patients diagnosed with substance dependence, along with control patients with no history of substance-related conditions, matched by age, gender, and status of HIV, hepatitis C, and sickle cell disease. The top machine learning classifier using all features achieved a mean area under the receiver operating characteristic (AUROC) curve of ~ 92%, and analysis of the model uncovered associations between basic clinical factors and substance dependence. Additionally, diagnoses, prescriptions, and procedures prior to the diagnoses of substance dependence were analyzed to elucidate the clinical profile of substance-dependent patients, relative to controls. CONCLUSIONS: The predictive model may hold utility for identifying patients at risk of developing dependence, risk of overdose, and opioid-seeking patients that report other symptoms in their visits to the emergency room.

Chemogenetics revealed: DREADD occupancy and activation via converted clozapine.

The chemogenetic technology DREADD (designer receptors exclusively activated by designer drugs) is widely used for remote manipulation of neuronal activity in freely moving animals. DREADD technology posits the use of "designer receptors," which are exclusively activated by the "designer drug" clozapine N-oxide (CNO). Nevertheless, the in vivo mechanism of action of CNO at DREADDs has never been confirmed. CNO does not enter the brain after systemic drug injections and shows low affinity for DREADDs. Clozapine, to which CNO rapidly converts in vivo, shows high DREADD affinity and potency. Upon systemic CNO injections, converted clozapine readily enters the brain and occupies central nervous system-expressed DREADDs, whereas systemic subthreshold clozapine injections induce preferential DREADD-mediated behaviors.