Explore the vast range of titles available.

Tobacco harm reduction is a public health approach to reduce the impact of cigarette smoking on individuals. Non-combustible alternatives to cigarettes, such as electronic cigarettes (e-cigarettes), deliver nicotine to the user in the absence of combustion. The absence of combustion in e-cigarettes reduces the level of harmful or potentially harmful chemicals in the aerosol generated. This narrative review examines the published literature that studied the chemistry of e-cigarette aerosols, the related toxicology in cell culture and animal models, as well as clinical studies that investigated short- and long-term changes in biomarkers of smoke exposure after switching to e-cigarettes. In the context of the literature reviewed, the evidence supports the harm reduction potential for adult smokers who switch to e-cigarettes.

Sex differences exist in behaviors, disease and neuropsychiatric disorders. Sexual dimorphisms however, have yet to be studied across the whole brain and across a comprehensive time course of postnatal development. Here, we use manganese-enhanced MRI (MEMRI) to longitudinally image male and female C57BL/6J mice across 9 time points, beginning at postnatal day 3. We recapitulate findings on canonically dimorphic areas, demonstrating MEMRI’s ability to study neuroanatomical sex differences. We discover, upon whole-brain volume correction, that neuroanatomical regions larger in males develop earlier than those larger in females. Groups of areas with shared sexually dimorphic developmental trajectories reflect behavioral and functional networks, and expression of genes involved with sex processes. Also, post-pubertal neuroanatomy is highly individualized, and individualization occurs earlier in males. Our results demonstrate the ability of MEMRI to reveal comprehensive developmental differences between male and female brains, which will improve our understanding of sex-specific predispositions to various neuropsychiatric disorders. Sex differences occur in various aspects of neurodevelopment. Here the authors use manganese-enhanced MRI at nine different postnatal stages to detail the development of structural sex differences in the mouse brain.

Alterations in the gut microbiome have been linked to a variety of mental illnesses including anxiety and depression. This study utilized advanced bioinformatics tools that integrated both the compositional and community nature of gut microbiota to investigate how gut microbiota influence clinical symptoms in a sample of participants with depression. Gut microbiota of 179 participants with major depressive disorder (MDD) in the Texas Resilience Against Depression (T-RAD) study were analyzed by 16S rRNA gene sequencing of stool samples. Severity of anxiety, depression, and anhedonia symptoms were assessed with General Anxiety Disorder – 7 item scale, Patient Health 9-item Questionnaire, and Dimensional Anhedonia Rating Scale, respectively. Using weighted correlation network analysis, a data-driven approach, three co-occurrence networks of bacterial taxa were identified. One of these co-occurrence networks was significantly associated with clinical features including depression and anxiety. The hub taxa associated with this co-occurrence module –one Ruminococcaceae family taxon, one Clostridiales vadinBB60 group family taxon, and one Christencenellaceae family taxon– were connected to several additional butyrate-producing bacteria suggesting that deficits in butyrate production may contribute to clinical symptoms. Therefore, by considering the community nature of the gut microbiome in a real world clinical sample, this study identified a gut microbial co-occurrence network that was significantly associated with clinical anxiety in a cohort of depressed individuals.

Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5–4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8–12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.

Multisite collection and preservation of peripheral blood mononuclear cells (PBMCs) for centralized analysis is an indispensable strategy for large cohort immune phenotyping studies. However, the absence of cross-site standardized protocols introduces unnecessary sample variance. Here we describe the protocol implemented by the Province of Ontario Neurodevelopmental Disorders (POND) Network's immune platform for the multisite collection, processing, and cryopreservation of PBMCs. We outline quality control standards and evaluate the performance of our PBMC processing and storage protocol. We also describe the Child Immune History Questionnaire results, an assessment tool evaluating pre-existing immune conditions in children with neurodevelopmental disorders (NDDs). Cell viability was assessed in samples from 178 participants based on strict quality control criteria. Overall, 83.1% of samples passed quality control standards. Samples collected and processed at the same site had higher quality control pass rates than samples that were collected and subsequently shipped to another site for processing. We investigated if freezer time impacted sample viability and found no difference in mean freezer time between samples that passed and failed quality control. The Child Immune History Questionnaire had a response rate of 87.1%. The described protocol produces viable samples that may be used in future immune phenotyping experiments.

Gene-environment interactions in the postnatal period have a long-term impact on neurodevelopment. To effectively assess neurodevelopment in the mouse, we developed a behavioural pipeline that incorporates several validated behavioural tests to measure translationally relevant milestones of behaviour in mice. The behavioral phenotype of 1060 wild type and genetically-modified mice was examined followed by structural brain imaging at 4 weeks of age. The influence of genetics, sex, and early life stress on behaviour and neuroanatomy was determined using traditional statistical and machine learning methods. Analytical results demonstrated that neuroanatomical diversity was primarily associated with genotype whereas behavioural phenotypic diversity was observed to be more susceptible to gene-environment variation. We describe a standardized mouse phenotyping pipeline, termed the Developmental Behavioural Milestones (DBM) Pipeline released alongside the 1000 Mouse Developmental Behavioural Milestones (1000 Mouse DBM) database to institute a novel framework for reproducible interventional neuroscience research.

Maternal diet and metabolic conditions, such as obesity and diabetes, are associated with consequences for offspring brain health, including effects on behaviour and an increased risk for neurodevelopmental disorders (NDDs). The extent and sequence of neuroanatomical changes to offspring brain development produced by dietary conditions have not yet been reported. In this study, we used a mouse model of parental high-fat or high-fat/high-sugar diet consumption to examine its effects on offspring brain development using longitudinal magnetic resonance imaging. We demonstrated that exposure to these parental diets through gestation and lactation resulted in offspring brain structure changes. Different temporal patterns of change were observed: some structures exhibited volume differences already at postnatal day 3; some of these early appearing changes diminished early in development while others were still present in adulthood; other structure changes were found to emerge later in the pubertal period. Brain changes in adulthood were present despite switching to a healthy diet at weaning. Brain regions impacted included the cingulate cortex, subregions of the hippocampus, and the orbitofrontal cortex, regions previously reported as affected in human NDD populations, with functional roles in reward processing and social cognition, memory, and decision making, respectively. Affected cortical regions, including the cingulate and orbitofrontal cortex, were found to be increased in volume relative to the whole brain, while affected subcortical regions were largely decreased in volume. Our data provide new insights into the long-term neuroanatomical impact of parental diets and how those diets may impact NDD risk. Future studies could use this model to evaluate preventative or ameliorative measures.

Monitoring sleep and activity through wearable devices such as wrist-worn actigraphs has the potential for long-term measurement in the individual’s own environment. Long periods of data collection require a complex approach, including standardized pre-processing and data trimming, and robust algorithms to address non-wear and missing data. In this study, we used a data-driven approach to quality control, pre-processing and analysis of longitudinal actigraphy data collected over the course of 1 year in a sample of 95 participants. We implemented a data processing pipeline using open-source packages for longitudinal data thereby providing a framework for treating missing data patterns, non-wear scoring, sleep/wake scoring, and conducted a sensitivity analysis to demonstrate the impact of non-wear and missing data on the relationship between sleep variables and depressive symptoms. Compliance with actigraph wear decreased over time, with missing data proportion increasing from a mean of 4.8% in the first week to 23.6% at the end of the 12 months of data collection. Sensitivity analyses demonstrated the importance of defining a pre-processing threshold, as it substantially impacts the predictive value of variables on sleep-related outcomes. We developed a novel non-wear algorithm which outperformed several other algorithms and a capacitive wear sensor in quality control. These findings provide essential insight informing study design in digital health research.

There is limited literature on associations between inflammatory tone and response to sequential pharmacotherapies in major depressive disorder (MDD). In a 16-week open-label clinical trial, 211 participants with MDD were treated with escitalopram 10-20 mg daily for 8 weeks. Responders continued escitalopram while non-responders received adjunctive aripiprazole 2-10 mg daily for 8 weeks. Plasma levels of pro-inflammatory markers-C-reactive protein, interleukin (IL)-1β, IL-6, IL-17, interferon-gamma (IFN)-Γ, tumor necrosis factor (TNF)-α, and Chemokine C-C motif ligand-2 (CCL-2)-measured at baseline, and after 2, 8 and 16 weeks were included in logistic regression analyzes to assess associations between inflammatory markers and treatment response. Pre-treatment IFN-Γ and CCL-2 levels were significantly associated with a lower of odds of response to escitalopram at 8 weeks. Increases in CCL-2 levels from weeks 8 to 16 in escitalopram non-responders were significantly associated with higher odds of non-response to adjunctive aripiprazole at week 16. Higher pre-treatment levels of IFN-Γ and CCL-2 were associated with non-response to escitalopram. Increasing levels of these pro-inflammatory markers may be associated with non-response to adjunctive aripiprazole. These findings require validation in independent clinical populations.

Cytochrome P450 drug-metabolizing enzymes may contribute to interindividual differences in antidepressant outcomes. We investigated the effects of CYP2C19 and CYP2D6 gene variants on response, tolerability, and serum concentrations. Patients ( N  = 178) were treated with escitalopram (ESC) from weeks 0–8 (Phase I), and at week 8, either continued ESC if they were responders or were augmented with aripiprazole (ARI) if they were non-responders (<50% reduction in Montgomery–Åsberg Depression Rating Scale from baseline) for weeks 8–16 (Phase II). Our results showed that amongst patients on ESC-Only, CYP2C19 intermediate and poor metabolizers (IM + PMs), with reduced or null enzyme function, trended towards significantly lower symptom improvement during Phase II compared to normal metabolizers (NMs), which was not observed in ESC + ARI. We further showed that CYP2D6 NMs and IM + PMs had a higher likelihood of reporting a treatment-related central nervous system side effect in ESC-Only and ESC + ARI, respectively. The differences in the findings between ESC-Only and ESC + ARI may be due to the altered pharmacokinetics of ESC by ARI coadministration in ESC + ARI. We provided evidence for this postulation when we showed that in ESC-Only, CYP2C19 and CYP2D6 IM + PMs demonstrated significantly higher ESC concentrations at Weeks 10 and 16 compared to NMs. In contrast, ESC + ARI showed an association with CYP2C19 but not with CYP2D6 metabolizer group. Instead, ESC + ARI showed an association between CYP2D6 metabolizer group and ARI metabolite-to-drug ratio suggesting potential competition between ESC and ARI for CYP2D6. Our findings suggest that dosing based on CYP2C19 and CYP2D6 genotyping could improve safety and outcome in patients on ESC monotherapy.