PI3K/mTOR is a therapeutically targetable genetic dependency in diffuse intrinsic pontine glioma

Diffuse midline glioma (DMG), including tumors diagnosed in the brainstem (diffuse intrinsic pontine glioma; DIPG), are uniformly fatal brain tumors that lack effective treatment. Analysis of CRISPR/Cas9 loss-of-function gene deletion screens identified PIK3CA and MTOR as targetable molecular dependencies across patient derived models of DIPG, highlighting the therapeutic potential of the blood-brain barrier–penetrant PI3K/Akt/mTOR inhibitor, paxalisib. At the human-equivalent maximum tolerated dose, mice treated with paxalisib experienced systemic glucose feedback and increased insulin levels commensurate with patients using PI3K inhibitors. To exploit genetic dependence and overcome resistance while maintaining compliance and therapeutic benefit, we combined paxalisib with the antihyperglycemic drug metformin. Metformin restored glucose homeostasis and decreased phosphorylation of the insulin receptor in vivo, a common mechanism of PI3K-inhibitor resistance, extending survival of orthotopic models. DIPG models treated with paxalisib increased calcium-activated PKC signaling. The brain penetrant PKC inhibitor enzastaurin, in combination with paxalisib, synergistically extended the survival of multiple orthotopic patient-derived and immunocompetent syngeneic allograft models; benefits potentiated in combination with metformin and standard-of-care radiotherapy. Therapeutic adaptation was assessed using spatial transcriptomics and ATAC-Seq, identifying changes in myelination and tumor immune microenvironment crosstalk. Collectively, this study has identified what we believe to be a clinically relevant DIPG therapeutic combinational strategy

Fatigue and physical disability in patients with multiple sclerosis: a structural equation modeling approach

Although fatigue is one of the most common and disabling symptoms in patients with multiple sclerosis (MS), its pathogenesis is still poorly understood and it is difficult to treat. The aim of the current study was to test the assumptions of a cognitive-behavioral model that explains fatigue and physical disability in MS patients, by comparing this approach with a more traditional biomedical approach. Structural equation modeling was applied to a sample of 262 MS patients. Neither the cognitive-behavioral, nor the biomedical model showed an adequate fit of our data. The modification indices supported an integration of both models, which showed a better fit than those of the separate models. This final model, is notable for at least three features: (1) fatigue is associated with depression and physical disability, (2) physical disability is associated with disease severity and fatigue-related fear and avoidance behavior, and (3) catastrophic interpretations about fatigue, fueled by depression, mediated the relationship between fatigue and fatigue-related fear and avoidance behavior. Our results suggest that an integrated approach, including the modification of catastrophic thoughts about fatigue, would be beneficial in the treatment of fatigue in MS patients

Measurement error, time lag, unmeasured confounding: Considerations for longitudinal estimation of the effect of a mediator in randomised clinical trials.

Clinical trials are expensive and time-consuming and so should also be used to study how treatments work, allowing for the evaluation of theoretical treatment models and refinement and improvement of treatments. These treatment processes can be studied using mediation analysis. Randomised treatment makes some of the assumptions of mediation models plausible, but the mediator-outcome relationship could remain subject to bias. In addition, mediation is assumed to be a temporally ordered longitudinal process, but estimation in most mediation studies to date has been cross-sectional and unable to explore this assumption. This study used longitudinal structural equation modelling of mediator and outcome measurements from the PACE trial of rehabilitative treatments for chronic fatigue syndrome (ISRCTN 54285094) to address these issues. In particular, autoregressive and simplex models were used to study measurement error in the mediator, different time lags in the mediator-outcome relationship, unmeasured confounding of the mediator and outcome, and the assumption of a constant mediator-outcome relationship over time. Results showed that allowing for measurement error and unmeasured confounding were important. Contemporaneous rather than lagged mediator-outcome effects were more consistent with the data, possibly due to the wide spacing of measurements. Assuming a constant mediator-outcome relationship over time increased precision.Funding for the PACE trial was provided by the Medical Research Council, Department for Health for England, The Scottish Chief Scientist Office, and the Department for Work and Pensions. TC, AP and KG were in part supported by the National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, Psychology & Neuroscience, Kings College London. KG was also funded by an NIHR Doctoral Fellowship, DRF-2011-04-06

Genetic contributions to self-reported tiredness

Self-reported tiredness and low energy, often called fatigue, are associated with poorer physical and mental health. Twin studies have indicated that this has a heritability between 6 and 50%. In the UK Biobank sample (N=108 976), we carried out a genome-wide association study (GWAS) of responses to the question, ‘Over the last two weeks, how often have you felt tired or had little energy?’ Univariate GCTA-GREML found that the proportion of variance explained by all common single-nucleotide polymorphisms for this tiredness question was 8.4% (s.e.=0.6%). GWAS identified one genome-wide significant hit (Affymetrix id 1:64178756_C_T; P=1.36 × 10−11). Linkage disequilibrium score regression and polygenic profile score analyses were used to test for shared genetic aetiology between tiredness and up to 29 physical and mental health traits from GWAS consortia. Significant genetic correlations were identified between tiredness and body mass index (BMI), C-reactive protein, high-density lipoprotein (HDL) cholesterol, forced expiratory volume, grip strength, HbA1c, longevity, obesity, self-rated health, smoking status, triglycerides, type 2 diabetes, waist–hip ratio, attention deficit hyperactivity disorder, bipolar disorder, major depressive disorder, neuroticism, schizophrenia and verbal-numerical reasoning (absolute rg effect sizes between 0.02 and 0.78). Significant associations were identified between tiredness phenotypic scores and polygenic profile scores for BMI, HDL cholesterol, low-density lipoprotein cholesterol, coronary artery disease, C-reactive protein, HbA1c, height, obesity, smoking status, triglycerides, type 2 diabetes, waist–hip ratio, childhood cognitive ability, neuroticism, bipolar disorder, major depressive disorder and schizophrenia (standardised β’s had absolute values<0.03). These results suggest that tiredness is a partly heritable, heterogeneous and complex phenomenon that is phenotypically and genetically associated with affective, cognitive, personality and physiological processes

Predicting fatigue in patients using home parenteral nutrition: a longitudinal study

Background: Home parenteral nutrition (HPN) is a lifesaving therapy for patients with diseases that preclude adequate oral or enteral food intake. HPN has a large impact on daily life. Many patients suffer from fatigue and depression, and they experience limits in social activities. This all contributes to a lower quality of life.Purpose: Fatigue is the most frequently mentioned problem in Dutch HPN patients. Therefore, we studied the prevalence, course and predictors of fatigue in these patients.Methods: Patients completed questionnaires at baseline and follow-up (12 months later). Measurements included fatigue, depression, functional impairment, social support, self-efficacy, coping, anxiety and acceptance. Laboratory measures, including total bilirubin, creatinine, albumin and haemoglobin levels, were obtained from the medical records. Descriptive statistics, correlations and linear regression analysis were performed.Results: The response rate was 71% (n=75). Sixty-five per cent of the patients were severely fatigued (n=49). Eighty-nine per cent experienced persistent fatigue. Baseline fatigue predicted 57% of the variance of fatigue at follow-up, and avoidance was responsible for 3% of the variance. No significant correlations between fatigue and laboratory measures were found. A cross-sectional analysis showedthat 46% of the variance of fatigue was explained by functional impairment, self-efficacy and depression.Conclusion: Severe fatigue is a persistent problem for HPNpatients. Baseline fatigue was the strongest predictor of fatigue at follow-up. Functional impairment, self-efficacy and depression are strongly related to fatigue. Early recognition and treatment of fatigue are important