Citations

TPS2075 Background: IDH mutant astrocytomas express high levels of 2-hydroxyglutarate (2-HG), an oncogenic metabolite which drives gliomagenesis. Excess 2-HG inhibits branched chain amino acid transaminase, which catalyzes glutamate synthesis from branched chain amino acids. This defect causes these tumors to become more reliant on glutaminase for glutamate biosynthesis from glutamine. CB-839 (telaglenastat) is a novel glutaminase inhibitor which is well tolerated in humans. McBrayer et al have recently demonstrated that CB-839 further depletes intracellular glutamate and glutathione in IDH mutant glioma cells, and enhances RT (radiation therapy) efficacy in an orthotopic glioma model. Methods: NCI #10218 is a CTEP supported phase I clinical trial investigating the safety and tolerability of CB-839 when combined with RT/TMZ (temozolomide) in patients with previously untreated IDH mutant grade II/III astrocytoma. Patients with grade II and III astrocytomas will be treated with 50.4 and 59.4 Gy of RT, respectively, with standard doses of concurrent TMZ. CB-839 will also be administered orally concurrently with RT, with doses escalated in cohorts based on a standard 3+3 design. After defining the maximum tolerated dose (MTD) of CB-839, an expansion cohort will evaluate the pre- and post-CB-839 therapy metabolome of patients with IDH mutant astrocytoma. Enrollment to this cohort will require measurable disease and patients will additionally be treated with a 7 day run-in of CB-839 at MTD prior to RT. The effect of CB-839 on the metabolome will be studied in both plasma (LC/MS/MS) and tumor (magnetic resonance spectroscopy), along with PK to confirm adequacy of systemic exposure. Preliminary data on neurocognitive endpoints will also be acquired. NCI #10218 is currently activated for enrollment to cohort 1. Clinical trial information: NCT03528642.

We consider the problem of model‐based clustering in the presence of many correlated, mixed continuous, and discrete variables, some of which may have missing values. Discrete variables are treated with a latent continuous variable approach, and the Dirichlet process is used to construct a mixture model with an unknown number of components. Variable selection is also performed to identify the variables that are most influential for determining cluster membership. The work is motivated by the need to cluster patients thought to potentially have autism spectrum disorder on the basis of many cognitive and/or behavioral test scores. There are a modest number of patients (486) in the data set along with many (55) test score variables (many of which are discrete valued and/or missing). The goal of the work is to (1) cluster these patients into similar groups to help identify those with similar clinical presentation and (2) identify a sparse subset of tests that inform the clusters in order to eliminate unnecessary testing. The proposed approach compares very favorably with other methods via simulation of problems of this type. The results of the autism spectrum disorder analysis suggested 3 clusters to be most likely, while only 4 test scores had high (>0.5) posterior probability of being informative. This will result in much more efficient and informative testing. The need to cluster observations on the basis of many correlated, continuous/discrete variables with missing values is a common problem in the health sciences as well as in many other disciplines.

Abstract Although the precise drug mechanism of action of acamprosate remains unclear, its antidipsotropic effect is mediated in part through glutamatergic neurotransmission. We evaluated the effect of 4 weeks of acamprosate treatment in a cohort of 13 subjects with alcohol dependence (confirmed by a structured interview, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision) on proton magnetic resonance spectroscopy glutamate levels in the midline anterior cingulate cortex (MACC). We compared levels of metabolites with a group of 16 healthy controls. The Pennsylvania Alcohol Craving Scale was used to assess craving intensity. At baseline, before treatment, the mean cerebrospinal fluid–corrected MACC glutamate (Glu) level was significantly elevated in subjects with alcohol dependence compared with controls (P = 0.004). Four weeks of acamprosate treatment reduced glutamate levels (P = 0.025), an effect that was not observed in subjects who did not take acamprosate. At baseline, there was a significant positive correlation between cravings, measured by the Pennsylvania Alcohol Craving Scale, and MACC (Glu) levels (P = 0.019). Overall, these data would suggest a normalizing effect of acamprosate on a hyperglutamatergic state observed in recently withdrawn patients with alcohol dependence and a positive association between MACC glutamate levels and craving intensity in early abstinence. Further research is needed to evaluate the use of these findings for clinical practice, including monitoring of craving intensity and individualized selection of treatment with antidipsotropic medications in subjects with alcohol dependence.

Background: The relationship between cortical lesions (CLs) and white matter lesions (WMLs) in multiple sclerosis (MS) is poorly understood. Pathological studies support a topographical association between CLs and underlying subcortical WMLs and suggest CLs may play a role in both disease initiation and progression. We hypothesized that cortical MS lesions are physically connected to white matter MS lesions via axonal connections. Objective: To assess the presence of CL-WML connectivity utilizing novel magnetic resonance imaging (MRI) methodology. Methods: In all, 28 relapsing-remitting MS patients and 25 controls received 3 T MRI scans, including double inversion recovery (DIR) for CL detection coupled with diffusion tensor imaging (DTI). CL and WML maps were created, and DTI was used to calculate inter-lesional connectivity and volumetric connectivity indices. Results: All patients showed inter-lesional WML connectivity (median 76% of WMLs connected to another WML; interquartile range (IQR), 58%–88%). On average, 52% of detected CLs per patient were connected to at least one WML (IQR, 42%–71%). Volumetric connectivity analysis showed significantly elevated cortical lesion ratios in MS patients (median, 2.3; IQR, 1.6–3.3) compared to null MS and healthy control datasets ( p < 0.001). Conclusion: These findings provide strong evidence of inter-lesional connectivity between CLs and WMLs, supporting our hypothesis of intrinsic CL-WML connectivity.

BackgroundQuantifying craving longitudinally during the course of withdrawal, early abstinence, and relapse is essential for optimal management of alcohol use disorder (AUD). In an effort to identify biological correlates of craving, we used proton magnetic resonance spectroscopy (1H‐MRS) to investigate the correlation between craving and glutamate levels in the left dorsolateral prefrontal cortex (LDLPFC) of patients with AUD.MethodsParticipants underwent 1H‐MRS of the LDLPFC with 2‐dimensional J‐resolved (2DJ) averaged PRESS. MRS data were processed with LCModel and cerebrospinal fluid (CSF)‐corrected to generate metabolite concentrations. The Penn Alcohol Craving Scale (PACS) and the 30‐day time line follow‐back (TLFB 30) were used to quantify craving for alcohol and drinking patterns, respectively.ResultsThere was a statistically significant positive correlation between CSF‐corrected glutamate ([Glu]) levels and PACS scores (n = 14; p = 0.005). When PACS scores were dichotomized (< or ≥median = 16), [Glu] levels were significantly higher in the high‐ versus low‐craving group (p = 0.007). In addition, there was a significant negative correlation between CSF‐corrected N‐acetyl aspartic acid ([NAA]) levels and mean number of drinks per drinking day in the past month (n = 13; TLFB 30; p = 0.012). When mean TLFB 30 was dichotomized (< or ≥median = 7.86), [NAA] levels were significantly lower in subjects that consumed more alcoholic beverages. There was no significant correlation between [Glu] and [NAA] levels with other measures of drinking behavior and or depression symptom severity.ConclusionsWhile limited by small sample size, these data suggest that glutamate levels in LDLPFC are associated with alcohol craving intensity in patients with AUD. Further study with larger sample size is needed to replicate this finding and evaluate the merits of glutamate spectroscopy as a biological correlate of alcohol craving intensity and a guide to treatment interventions.

Objective: Preliminary studies suggest that repetitive transcranial magnetic stimulation (rTMS) may be an effective and tolerable intervention for adolescents with treatment-resistant depression. There is limited rationale to inform coil placement for rTMS dosing in this population. We sought to examine and compare three localization techniques for coil placement in the context of an open-label trial of high-frequency rTMS for adolescents with treatment-resistant depression. Methods: Ten adolescents with treatment-resistant depression were enrolled in an open-label trial of high-frequency rTMS. Participants were offered 30 rTMS sessions (10 Hz, 120% motor threshold, left 3000 pulses applied to the dorsolateral prefrontal cortex) over 6–8 weeks. Coil placement for treatment was MRI guided. The scalp location for treatment was compared with the locations identified with standard 5 cm rule and Beam F3 methods. Results: Seven adolescents completed 30 rTMS sessions. No safety or tolerability concerns were identified. Depression severity as assessed with the Children's Depression Rating Scale Revised improved from baseline to treatment 10, treatment 20, and treatment 30. Gains in depressive symptom improvement were maintained at 6 month follow-up visits. An MRI-guided approach for coil localization was feasible and efficient. Our results suggest that the 5 cm rule, Beam F3, and the MRI-guided localization approaches provided variable scalp targets for rTMS treatment. Conclusions: Open-label, high-frequency rTMS was feasible, tolerable, and effective for adolescents with treatment-resistant depression. Larger, blinded, sham-controlled trials are needed for definitive safety and efficacy data. Further efforts to understand optimal delivery, dosing, and biomarker development for rTMS treatments of adolescent depression are warranted.

Context:Numerous factors are purported to influence insulin sensitivity including age, adiposity, mitochondrial function, and physical fitness. Univariate associations cannot address the complexity of insulin resistance or the interrelationship among potential determinants.Objective:The objective of the study was to identify significant independent predictors of insulin sensitivity across a range of age and adiposity in humans.Design, Setting, and Participants:Peripheral and hepatic insulin sensitivity were measured by two stage hyperinsulinemic-euglycemic clamps in 116 men and women (aged 19–78 y). Insulin-stimulated glucose disposal, the suppression of endogenous glucose production during hyperinsulinemia, and homeostatic model assessment of insulin resistance were tested for associations with 11 potential predictors. Abdominal subcutaneous fat, visceral fat (AFVISC), intrahepatic lipid, and intramyocellular lipid (IMCL) were quantified by magnetic resonance imaging and spectroscopy. Skeletal muscle mitochondrial respiratory capacity (state 3), coupling efficiency, and reactive oxygen species production were evaluated from muscle biopsies. Aerobic fitness was measured from whole-body maximum oxygen uptake (VO2 peak), and metabolic flexibility was determined using indirect calorimetry.Results:Multiple regression analysis revealed that AFVISC (P &lt; .0001) and intrahepatic lipid (P = .002) were independent negative predictors of peripheral insulin sensitivity, whereas VO2 peak (P = .0007) and IMCL (P = .023) were positive predictors. Mitochondrial capacity and efficiency were not independent determinants of peripheral insulin sensitivity. The suppression of endogenous glucose production during hyperinsulinemia model of hepatic insulin sensitivity revealed percentage fat (P &lt; .0001) and AFVISC (P = .001) as significant negative predictors. Modeling homeostatic model assessment of insulin resistance identified AFVISC (P &lt; .0001), VO2 peak (P = .001), and IMCL (P = .01) as independent predictors.Conclusion:The reduction in insulin sensitivity observed with aging is driven primarily by age-related changes in the content and distribution of adipose tissue and is independent of muscle mitochondrial function or chronological age.