Search

Increasing knowledge of the genome sequences of several organisms and the development of genome-wide, high-throughput screening techniques for gene expression are likely to generate a vast amount of data aimed at elucidating the molecular mechanisms of addiction. These findings are likely to have potential for future addiction pharmacotherapies. However, it is important to employ animal models that dissociate the molecular and cellular consequences of the direct pharmacological effects of addictive drugs from those that result from the cognitive processes associated with self-administration of these drugs. In this article, we suggest that the short-term and long-term neuroadaptive effects of addictive drugs in the brain depend crucially on the drug-exposure paradigm used [i.e. passive (non-contingent) drug exposure and active (contingent) self-administration]. This has important ramifications for future molecular and cellular studies of drug addiction.

Adaptation of circadian rhythms to the environmental light-dark cycle is necessary for the survival of organisms. This synchronization or entrainment is only caused by light (photic input) during the dark period, according to the internal biological clock of an organism. During the light period, internal factors (non-photic input), rather than light, are able to entrain circadian rhythms. In this article, the data that implicate the neurotransmitter system for histamine in circadian entrainment are reviewed. Furthermore, we speculate that histamine receptors are the final gate at which both photic and non-photic entrainment mechanisms converge before sending a resetting signal to the intracellular biological clock.

The mammalian circadian system is composed of a light-entrainable central clock in the suprachiasmatic nuclei (SCN) of the brain and peripheral clocks in virtually any other tissue. It allows the organism to optimally adjust metabolic, physiological and behavioral functions to the physiological needs it will have at specific time of the day. According to the resonance theory, such rhythms are only advantageous to an organism when in tune with the environment, which is illustrated by the adverse health effects originating from chronic circadian disruption by jetlag and shift work. Using short-period Cry1 and long-period Cry2 deficient mice as models for morningness and eveningness, respectively, we explored the effect of chronotype on the phase relationship between the central SCN clock and peripheral clocks in other organs. Whereas the behavioral activity patterns and circadian gene expression in the SCN of light-entrained Cry1-/- and Cry2-/- mice largely overlapped with that of wild type mice, expression of clock and clock controlled genes in liver, kidney, small intestine, and skin was shown to be markedly phase-advanced or phase-delayed, respectively. Likewise, circadian rhythms in urinary corticosterone were shown to display a significantly altered phase relationship similar to that of gene expression in peripheral tissues. We show that the daily dissonance between peripheral clocks and the environment did not affect the lifespan of Cry1-/- or Cry2-/- mice. Nonetheless, the phase-shifted peripheral clocks in light-entrained mice with morningness and eveningness-like phenotypes may have implications for personalized preventive and therapeutic (i.e. chronomodulation-based) health care for people with early and late chronotypes. [ABSTRACT FROM AUTHOR]

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to judge whether metabolite levels are abnormal. However, a large number of reference samples requires the use of out-of-batch samples, which is hampered by the semi-quantitative nature of untargeted metabolomics data, i.e., technical variations between batches. Methods to merge and accurately normalize data from multiple batches are urgently needed. Based on six metrics, we compared the existing normalization methods on their ability to reduce the batch effects from nine independently processed batches. Many of those showed marginal performances, which motivated us to develop Metchalizer, a normalization method that uses 10 stable isotope-labeled internal standards and a mixed effect model. In addition, we propose a regression model with age and sex as covariates fitted on reference samples that were obtained from all nine batches. Metchalizer applied on log-transformed data showed the most promising performance on batch effect removal, as well as in the detection of 195 known biomarkers across 49 IEM patient samples and performed at least similar to an approach utilizing 15 within-batch reference samples. Furthermore, our regression model indicates that 6.5–37% of the considered features showed significant age-dependent variations. Our comprehensive comparison of normalization methods showed that our Log-Metchalizer approach enables the use out-of-batch reference samples to establish clinically-relevant reference values for metabolite concentrations. These findings open the possibilities to use large scale out-of-batch reference samples in a clinical setting, increasing the throughput and detection accuracy. [ABSTRACT FROM AUTHOR]

Presents a study which examined the long-term effects of heroin exposure on the expression in the nucleus accumbens core of gene transcripts. Possible role of response contingency in the mediation of heroin-induced gene expression; Observations on the differential expression of gene transcripts; Conclusions and significance.

Metachromatic leukodystrophy is a lethal metabolic leukodystrophy, with emerging treatments for early disease stages. Biomarkers to measure disease activity are required for clinical assessment and treatment follow-up. This retrospective study compared neurofilament light chain and glial fibrillary acidic protein (GFAP) levels in CSF (n = 11) and blood (n = 92) samples of 40 patients with metachromatic leukodystrophy (aged 0-42 years) with 38 neurologically healthy children (aged 0-17 years) and 38 healthy adults (aged 18-45 years), and analysed the associations between these levels with clinical phenotype and disease evolution in untreated and transplanted patients. Metachromatic leukodystrophy subtype was determined based on the (expected) age of symptom onset. Disease activity was assessed by measuring gross motor function deterioration and brain MRI. Longitudinal analyses with measurements up to 23 years after diagnosis were performed using linear mixed models. CSF and blood neurofilament light chain and GFAP levels in paediatric controls were negatively associated with age (all P < 0.001). Blood neurofilament light chain level at diagnosis (median, interquartile range; picograms per millilitre) was significantly increased in both presymptomatic (14.7, 10.6-56.7) and symptomatic patients (136, 40.8-445) compared to controls (5.6, 4.5-7.1), and highest among patients with late-infantile (456, 201-854) or early-juvenile metachromatic leukodystrophy (291.0, 104-445) and those ineligible for treatment based on best practice (291, 57.4-472). GFAP level (median, interquartile range; picogram per millilitre) was only increased in symptomatic patients (591, 224-1150) compared to controls (119, 78.2-338) and not significantly associated with treatment eligibility (P = 0.093). Higher blood neurofilament light chain and GFAP levels at diagnosis were associated with rapid disease progression in late-infantile (P = 0.006 and P = 0.051, respectively) and early-juvenile patients (P = 0.048 and P = 0.039, respectively). Finally, blood neurofilament light chain and GFAP levels decreased during follow-up in untreated and transplanted patients but remained elevated compared with controls. Only neurofilament light chain levels were associated with MRI deterioration (P < 0.001). This study indicates that both proteins may be considered as non-invasive biomarkers for clinical phenotype and disease stage at clinical assessment, and that neurofilament light chain might enable neurologists to make better informed treatment decisions. In addition, neurofilament light chain holds promise assessing treatment response. Importantly, both biomarkers require paediatric reference values, given that their levels first decrease before increasing with advancing age., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to judge whether metabolite levels are abnormal. However, a large number of reference samples requires the use of out-of-batch samples, which is hampered by the semi-quantitative nature of untargeted metabolomics data, i.e., technical variations between batches. Methods to merge and accurately normalize data from multiple batches are urgently needed. Based on six metrics, we compared the existing normalization methods on their ability to reduce the batch effects from nine independently processed batches. Many of those showed marginal performances, which motivated us to develop Metchalizer , a normalization method that uses 10 stable isotope-labeled internal standards and a mixed effect model. In addition, we propose a regression model with age and sex as covariates fitted on reference samples that were obtained from all nine batches. Metchalizer applied on log-transformed data showed the most promising performance on batch effect removal, as well as in the detection of 195 known biomarkers across 49 IEM patient samples and performed at least similar to an approach utilizing 15 within-batch reference samples. Furthermore, our regression model indicates that 6.5-37% of the considered features showed significant age-dependent variations. Our comprehensive comparison of normalization methods showed that our Log-Metchalizer approach enables the use out-of-batch reference samples to establish clinically-relevant reference values for metabolite concentrations. These findings open the possibilities to use large scale out-of-batch reference samples in a clinical setting, increasing the throughput and detection accuracy.

Pompe disease is an autosomal recessive lysosomal storage disorder characterized by progressive muscle weakness. The disease is caused by mutations in the acid α-glucosidase (GAA) gene. Despite the currently available enzyme replacement therapy (ERT), roughly half of the infants with Pompe disease die before the age of 3 years. Limitations of ERT are immune responses to the recombinant enzyme, incomplete correction of the disease phenotype, lifelong administration, and inability of the enzyme to cross the blood-brain barrier. We previously reported normalization of glycogen in heart tissue and partial correction of the skeletal muscle phenotype by ex vivo hematopoietic stem cell gene therapy. In the present study, using a codon-optimized GAA ( GAAco ), the enzyme levels resulted in close to normalization of glycogen in heart, muscles, and brain, and in complete normalization of motor function. A large proportion of microglia in the brain was shown to be GAA positive. All astrocytes contained the enzyme, which is in line with mannose-6-phosphate receptor expression and the key role in glycogen storage and glucose metabolism. The lentiviral vector insertion site analysis confirmed no preference for integration near proto-oncogenes. This correction of murine Pompe disease warrants further development toward a cure of the human condition., (© 2020 The Author(s).)

Mitochondrial neurogastrointestinal encephalomyopathy (MNGIE) is an autosomal recessive disorder caused by thymidine phosphorylase (TP) deficiency resulting in systemic accumulation of thymidine (d-Thd) and deoxyuridine (d-Urd) and characterized by early-onset neurological and gastrointestinal symptoms. Long-term effective and safe treatment is not available. Allogeneic bone marrow transplantation may improve clinical manifestations but carries disease and transplant-related risks. In this study, lentiviral vector-based hematopoietic stem cell gene therapy (HSCGT) was performed in Tymp -/- Upp1 -/- mice with the human phosphoglycerate kinase (PGK) promoter driving TYMP . Supranormal blood TP activity reduced intestinal nucleoside levels significantly at low vector copy number (median, 1.3; range, 0.2-3.6). Furthermore, we covered two major issues not addressed before. First, we demonstrate aberrant morphology of brain astrocytes in areas of spongy degeneration, which was reversed by HSCGT. Second, long-term follow-up and vector integration site analysis were performed to assess safety of the therapeutic LV vectors in depth. This report confirms and supplements previous work on the efficacy of HSCGT in reducing the toxic metabolites in Tymp -/- Upp1 -/- mice, using a clinically applicable gene transfer vector and a highly efficient gene transfer method, and importantly demonstrates phenotypic correction with a favorable risk profile, warranting further development toward clinical implementation.