The effect of older age on outcomes of rTMS treatment for treatment-resistant depression

Clinical outcomes of repetitive transcranial magnetic stimulation (rTMS) for treatment of treatment-resistant depression (TRD) vary widely and there is no mood rating scale that is standard for assessing rTMS outcome. It remains unclear whether TMS is as efficacious in older adults with late-life depression (LLD) compared to younger adults with major depressive disorder (MDD). This study examined the effect of age on outcomes of rTMS treatment of adults with TRD. Self-report and observer mood ratings were measured weekly in 687 subjects ages 16-100 years undergoing rTMS treatment using the Inventory of Depressive Symptomatology 30-item Self-Report (IDS-SR), Patient Health Questionnaire 9-item (PHQ), Profile of Mood States 30-item, and Hamilton Depression Rating Scale 17-item (HDRS). All rating scales detected significant improvement with treatment; response and remission rates varied by scale but not by age (response/remission ≥ 60: 38%-57%/25%-33%; <60: 32%-49%/18%-25%). Proportional hazards models showed early improvement predicted later improvement across ages, though early improvements in PHQ and HDRS were more predictive of remission in those < 60 years (relative to those ≥ 60) and greater baseline IDS burden was more predictive of non-remission in those ≥ 60 years (relative to those < 60). These results indicate there is no significant effect of age on treatment outcomes in rTMS for TRD, though rating instruments may differ in assessment of symptom burden between younger and older adults during treatment.

A comparison of self- and observer-rated scales for detecting clinical improvement during repetitive transcranial stimulation (rTMS) treatment of depression

Clinical outcomes of repetitive Transcranial Magnetic Stimulation (rTMS) for treatment of Major Depressive Disorder (MDD) vary widely, and no single mood rating scale is standard for assessing rTMS outcomes. This study of 708 subjects undergoing clinical rTMS compared the performance of four scales in measuring symptom change during rTMS treatment. Self-report and observer ratings were examined weekly with the Inventory of Depressive Symptomatology 30-item (IDS), Patient Health Questionnaire 9-item (PHQ), Profile of Mood States 30-item (POMS), and Hamilton Depression Rating Scale 17-item (HDRS). While all scales were correlated and detected significant improvement, the degree of improvement over time as well as response (33-50%) and remission (20-24%) rates varied significantly. Higher baseline severity was associated with lower likelihood of remission, and greater improvement by sessions 5 and 10 predicted response across all scales. Use of only a single scale to assess outcome conferred 14-36% risk of failing to detect response/remission indicated by another scale. The PHQ was most likely to indicate improvement and least likely to miss response or remission. These findings indicate that assessment of symptom burden during rTMS treatment may be most accurately assessed through use of multiple instruments.

Aerobic exercise enhances cognitive training effects in first-episode schizophrenia: randomized clinical trial demonstrates cognitive and functional gains

BACKGROUND

Cognitive training (CT) and aerobic exercise both show promising moderate impact on cognition and everyday functioning in schizophrenia. Aerobic exercise is hypothesized to increase brain-derived neurotrophic factor (BDNF) and thereby synaptic plasticity, leading to increased learning capacity. Systematic CT should take advantage of increased learning capacity and be more effective when combined with aerobic exercise.

METHODS

We examined the impact of a 6-month program of cognitive training & exercise (CT&E) compared to cognitive training alone (CT) in 47 first-episode schizophrenia outpatients. All participants were provided the same Posit Science computerized CT, 4 h/week, using BrainHQ and SocialVille programs. The CT&E group also participated in total body circuit training exercises to enhance aerobic conditioning. Clinic and home-based exercise were combined for a target of 150 min per week.

RESULTS

The MATRICS Consensus Cognitive Battery Overall Composite improved significantly more with CT&E than with CT alone (p = 0.04), particularly in the first 3 months (6.5 v. 2.2 T-score points, p < 0.02). Work/school functioning improved substantially more with CT&E than with CT alone by 6 months (p < 0.001). BDNF gain tended to predict the amount of cognitive gain but did not reach significance. The cognitive gain by 3 months predicted the amount of work/school functioning improvement at 6 months. The amount of exercise completed was strongly associated with the degree of cognitive and work/school functioning improvement.

CONCLUSIONS

Aerobic exercise significantly enhances the impact of CT on cognition and functional outcome in first-episode schizophrenia, apparently driven by the amount of exercise completed.

Exercise Predicts a Good Night's Sleep: Preliminary Findings from a UCLA Study of First-Episode Schizophrenia

BACKGROUND

Physical exercise can improve sleep quality in the general population. Understanding the negative impact of poor sleep quality on multiple domains of functioning among persons with schizophrenia is a new frontier of exploration. It is also imperative to investigate non-pharmacologic methods to improve sleep quality as these approaches may not carry the side effect burdens associated with medication.

OBJECTIVE

We examined the relationship between regular physical exercise and sleep quality among participants in an intervention consisting of both cognitive training and exercise.

METHODS

Participants (N = 48) were schizophrenia patients who had a first psychotic episode within two years of study entry. Participants received 4 h/week of internet-based cognitive training and an aerobic exercise program over a 6-month period. Sleep was assessed with the Pittsburgh Sleep Quality Index at baseline and six months later.

RESULTS

During the 3 months prior to the 6-month follow-up sleep assessment, participants completed an average of 12.6 group exercise sessions and an average of 12.9 individual at-home exercise sessions. A significant relationship between the number of exercise sessions and global sleep quality was seen at month six, r = -0.44, df = 39, p < 0.01. Group exercise frequency was also associated with improvement in global sleep quality over the six-month intervention, t(34) = -2.84, p = 0.008.

CONCLUSION

We demonstrated that a group of young adults with schizophrenia can be engaged in a regular exercise program, even during the tumultuous early course of the disorder. The number of exercise sessions in which they participated was associated with better sleep quality at six months and pre-postintervention improvement in sleep quality.

KEY MESSAGE

Improved sleep quality appears to be a benefit of regular exercise among individuals with serious mental illness.

A comprehensive benchmarking of WGS-based deletion structural variant callers

Advances in whole-genome sequencing (WGS) promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from WGS data presents a substantial number of challenges and a plethora of SV detection methods have been developed. Currently, evidence that investigators can use to select appropriate SV detection tools is lacking. In this article, we have evaluated the performance of SV detection tools on mouse and human WGS data using a comprehensive polymerase chain reaction-confirmed gold standard set of SVs and the genome-in-a-bottle variant set, respectively. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of the SV detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance as the SV detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low- and ultralow-pass sequencing data as well as for different deletion length categories.

Brain circuitry underlying the ABC model of anxiety

Anxiety Disorders are prevalent and often chronic, recurrent conditions that reduce quality of life. The first-line treatments, such as serotonin reuptake inhibitors and cognitive behavioral therapy, leave a significant proportion of patients symptomatic. As psychiatry moves toward targeted circuit-based treatments, there is a need for a theory that unites the phenomenology of anxiety with its underlying neural circuits. The Alarm, Belief, Coping (ABC) theory of anxiety describes how the neural circuits associated with anxiety interact with each other and domains of the anxiety symptoms, both temporally and spatially. The latest advancements in neuroimaging techniques offer the ability to assess these circuits in vivo. Using Neurosynth, a large open-access meta-analytic imaging database, the association between terms related to specific neural circuits was explored within the ABC theory framework. Alarm-related terms were associated with the amygdala, anterior cingulum, insula, and bed nucleus of stria terminalis. Belief-related terms were associated with medial prefrontal cortex, precuneus, bilateral temporal poles, and hippocampus. Coping-related terms were associated with the ventrolateral and dorsolateral prefrontal cortices, basal ganglia, and anterior cingulate. Neural connections underlying the functional neuroanatomy of the ABC model were observed. Additionally, there was considerable interaction and overlap between circuits associated with the symptom domains. Further neuroimaging research is needed to explore the dynamic interaction between the functional domains of the ABC theory. This will pave the way for probing the neuroanatomical underpinnings of anxiety disorders and provide an evidence-based foundation for the development of targeted treatments, such as neuromodulation.

Systematic benchmarking of omics computational tools

Computational omics methods packaged as software have become essential to modern biological research. The increasing dependence of scientists on these powerful software tools creates a need for systematic assessment of these methods, known as benchmarking. Adopting a standardized benchmarking practice could help researchers who use omics data to better leverage recent technological innovations. Our review summarizes benchmarking practices from 25 recent studies and discusses the challenges, advantages, and limitations of benchmarking across various domains of biology. We also propose principles that can make computational biology benchmarking studies more sustainable and reproducible, ultimately increasing the transparency of biomedical data and results.

Benchmarking studies are important for comprehensively understanding and evaluating different computational omics methods. Here, the authors review practices from 25 recent studies and propose principles to improve the quality of benchmarking studies.

Genome wide association analysis in a mouse advanced intercross line

The LG/J x SM/J advanced intercross line of mice (LG x SM AIL) is a multigenerational outbred population. High minor allele frequencies, a simple genetic background, and the fully sequenced LG and SM genomes make it a powerful population for genome-wide association studies. Here we use 1,063 AIL mice to identify 126 significant associations for 50 traits relevant to human health and disease. We also identify thousands of cis- and trans-eQTLs in the hippocampus, striatum, and prefrontal cortex of ~200 mice. We replicate an association between locomotor activity and Csmd1, which we identified in an earlier generation of this AIL, and show that Csmd1 mutant mice recapitulate the locomotor phenotype. Our results demonstrate the utility of the LG x SM AIL as a mapping population, identify numerous novel associations, and shed light on the genetic architecture of mammalian behavior.

Glyoxalase 1 and its substrate methylglyoxal are novel regulators of seizure susceptibility

PURPOSE

Epilepsy is a complex disease characterized by a predisposition toward seizures. There are numerous barriers to the successful treatment of epilepsy. For instance, current antiepileptic drugs have adverse side effects and variable efficacies. Furthermore, the pathophysiologic basis of epilepsy remains largely elusive. Therefore, investigating novel genes and biologic processes underlying epilepsy may provide valuable insight and enable the development of new therapeutic agents. We previously identified methylglyoxal (MG) as an endogenous γ-aminobutyric acid (GABAA ) receptor agonist. Here, we investigated the role of MG and its catabolic enzyme, glyoxalase 1 (GLO1), in seizures.

METHODS

We pretreated mice with MG before seizure induction with picrotoxin or pilocarpine and then assessed seizures behaviorally or by electroencephalography (EEG). We then investigated the role of GLO1 in seizures by treating mice with a pharmacologic inhibitor of GLO1 before seizure induction with pilocarpine and measured subsequent seizure phenotypes. Next, we explored the genetic relationship between Glo1 expression and seizures. We analyzed seizure phenotypes among C57BL/6J × DBA/2J (BXD) recombinant inbred (RI) mice with differential Glo1 expression. Lastly, we investigated a causal role for Glo1 in seizures by administering pilocarpine to transgenic (Tg) mice that overexpress Glo1.

KEY FINDINGS

Pretreatment with MG attenuated pharmacologically-induced seizures at both the behavioral and EEG levels. GLO1 inhibition, which increases MG concentration in vivo, also attenuated seizures. Among BXD RI mice, high Glo1 expression was correlated with increased seizure susceptibility. Tg mice overexpressing Glo1 displayed reduced MG concentration in the brain and increased seizure severity.

SIGNIFICANCE

These data identify MG as an endogenous regulator of seizures. Similarly, inhibition of GLO1 attenuates seizures, suggesting that this may be a novel therapeutic approach for epilepsy. Furthermore, this system may represent an endogenous negative feedback loop whereby high metabolic activity increases inhibitory tone via local accumulation of MG. Finally, Glo1 may contribute to the genetic architecture of epilepsy, as Glo1 expression regulates both MG concentration and seizure severity.

Role of Glyoxalase 1 (Glo1) and methylglyoxal (MG) in behavior: recent advances and mechanistic insights

Glyoxalase 1 (GLO1) is a ubiquitous cellular enzyme that participates in the detoxification of methylglyoxal (MG), a cytotoxic byproduct of glycolysis that induces protein modification (advanced glycation end-products, AGEs), oxidative stress, and apoptosis. The concentration of MG is elevated under high-glucose conditions, such as diabetes. As such, GLO1 and MG have been implicated in the pathogenesis of diabetic complications. Recently, findings have linked GLO1 to numerous behavioral phenotypes, including psychiatric diseases (anxiety, depression, schizophrenia, and autism) and pain. This review highlights GLO1's association with behavioral phenotypes, describes recent discoveries that have elucidated the underlying mechanisms, and identifies opportunities for future research.

Glyoxalase 1 increases anxiety by reducing GABAA receptor agonist methylglyoxal

Glyoxalase 1 (Glo1) expression has previously been associated with anxiety in mice; however, its role in anxiety is controversial, and the underlying mechanism is unknown. Here, we demonstrate that GLO1 increases anxiety by reducing levels of methylglyoxal (MG), a GABAA receptor agonist. Mice overexpressing Glo1 on a Tg bacterial artificial chromosome displayed increased anxiety-like behavior and reduced brain MG concentrations. Treatment with low doses of MG reduced anxiety-like behavior, while higher doses caused locomotor depression, ataxia, and hypothermia, which are characteristic effects of GABAA receptor activation. Consistent with these data, we found that physiological concentrations of MG selectively activated GABAA receptors in primary neurons. These data indicate that GLO1 increases anxiety by reducing levels of MG, thereby decreasing GABAA receptor activation. More broadly, our findings potentially link metabolic state, neuronal inhibitory tone, and behavior. Finally, we demonstrated that pharmacological inhibition of GLO1 reduced anxiety, suggesting that GLO1 is a possible target for the treatment of anxiety disorders.

Modulation ofTcf7l2 expression alters behavior in mice

The comorbidity of type 2 diabetes (T2D) with several psychiatric diseases is well established. While environmental factors may partially account for these co-occurrences, common genetic susceptibilities could also be implicated in the confluence of these diseases. In support of shared genetic burdens, TCF7L2, the strongest genetic determinant for T2D risk in the human population, has been recently implicated in schizophrenia (SCZ) risk, suggesting that this may be one of many loci that pleiotropically influence both diseases. To investigate whether Tcf7l2 is involved in behavioral phenotypes in addition to its roles in glucose metabolism, we conducted several behavioral tests in mice with null alleles of Tcf7l2 or overexpressing Tcf7l2. We identified a role for Tcf7l2 in anxiety-like behavior and a dose-dependent effect of Tcf7l2 alleles on fear learning. None of the mutant mice showed differences in prepulse inhibition (PPI), which is a well-established endophenotype for SCZ. These results show that Tcf7l2 alters behavior in mice. Importantly, these differences are observed prior to the onset of detectable glucose metabolism abnormalities. Whether these differences are related to human anxiety-disorders or schizophrenia remains to be determined. These animal models have the potential to elucidate the molecular basis of psychiatric comorbidities in diabetes and should therefore be studied further.

A role for casein kinase 1 epsilon in the locomotor stimulant response to methamphetamine

RATIONALE

We previously colocalized a quantitative trait locus (QTL) for sensitivity to the locomotor stimulant effects of methamphetamine (MA) with a QTL for expression of casein kinase 1 epsilon (Csnk1-epsilon) in the nucleus accumbens (NAc). Subsequently, we identified a single nucleotide polymorphism in CSNK1E (rs135745) that was associated with increased sensitivity to the subjective effects of d-amphetamine in healthy human subjects. Based on these results, we hypothesized that differential expression of Csnk1-epsilon causes differential sensitivity to MA-induced locomotor activity in mice.

OBJECTIVE

In the present study, we used PF-670462 (PF), which is a selective inhibitor of Csnk1-epsilon, to directly evaluate the role of Csnk1-epsilon in the locomotor stimulant response to MA in male C57BL/6J mice.

METHODS

We administered vehicle, PF, MA, or MA + PF, either via intraperitoneal injections or bilateral intra-NAc microinjections. We also examined Darpp-32 phosphorylation in mice receiving intraperitoneal injections.

RESULTS

Intraperitoneal PF (20-40 mg/kg) attenuated the locomotor stimulant response to MA (2 mg/kg) without affecting baseline activity. The high dose of PF also significantly inhibited MA-induced phosphorylation of Darpp-32, providing a potential mechanism by which Csnk1-epsilon contributes to MA-induced locomotor activity. Furthermore, microinjection of PF (5 microg/side) into the NAc completely blocked the locomotor stimulant response to MA (2.5 microg/side) without affecting baseline activity.

CONCLUSIONS

These results provide direct evidence that Csnk1-epsilon is crucial for the locomotor stimulant response to a moderate dose of MA and suggest that genetic polymorphisms affecting Csnk1-epsilon expression or function could influence sensitivity to amphetamines in both mice and humans.

A common and unstable copy number variant is associated with differences in Glo1 expression and anxiety-like behavior

Glyoxalase 1 (Glo1) has been implicated in anxiety-like behavior in mice and in multiple psychiatric diseases in humans. We used mouse Affymetrix exon arrays to detect copy number variants (CNV) among inbred mouse strains and thereby identified a ∼475 kb tandem duplication on chromosome 17 that includes Glo1 (30,174,390–30,651,226 Mb; mouse genome build 36). We developed a PCR-based strategy and used it to detect this duplication in 23 of 71 inbred strains tested, and in various outbred and wild-caught mice. Presence of the duplication is associated with a cis-acting expression QTL for Glo1 (LOD>30) in BXD recombinant inbred strains. However, evidence for an eQTL for Glo1 was not obtained when we analyzed single SNPs or 3-SNP haplotypes in a panel of 27 inbred strains. We conclude that association analysis in the inbred strain panel failed to detect an eQTL because the duplication was present on multiple highly divergent haplotypes. Furthermore, we suggest that non-allelic homologous recombination has led to multiple reversions to the non-duplicated state among inbred strains. We show associations between multiple duplication-containing haplotypes, Glo1 expression and anxiety-like behavior in both inbred strain panels and outbred CD-1 mice. Our findings provide a molecular basis for differential expression of Glo1 and further implicate Glo1 in anxiety-like behavior. More broadly, these results identify problems with commonly employed tests for association in inbred strains when CNVs are present. Finally, these data provide an example of biologically significant phenotypic variability in model organisms that can be attributed to CNVs.