Structural and parametric uncertainties in full Bayesian and graphical lasso based approaches: beyond edge weights in psychological networks

Uncertainty over model structures poses a challenge for many approaches exploring effect strength parameters at system-level. Monte Carlo methods for full Bayesian model averaging over model structures require considerable computational resources, whereas bootstrapped graphical lasso and its approximations offer scalable alternatives with lower complexity. Although the computational efficiency of graphical lasso based approaches has prompted growing number of applications, the restrictive assumptions of this approach are frequently ignored, such as its lack of coping with interactions. We demonstrate using an artificial and a real-world example that full Bayesian averaging using Bayesian networks provides detailed estimates through posterior distributions for structural and parametric uncertainties and it is a feasible alternative, which is routinely applicable in mid-sized biomedical problems with hundreds of variables. We compare Bayesian estimates with corresponding frequentist quantities from bootstrapped graphical lasso using pairwise Markov Random Fields, discussing also their interpretational differences. We present results using synthetic data from an artificial model and using the UK Biobank data set to explore a psychopathological network centered around depression (this research has been conducted using the UK Biobank Resource under Application Number 1602)

Neuropsychological and electrophysiological biomarkers of the schizophrenia spectrum

Schizophrenia is a neuropsychiatric disorder lying at the extreme of a spectrum of disorders that possibly share a common abnormality in neural connectivity. Efforts to reverse the core cognitive manifestations of schizophrenia using drug treatments have so far been unsuccessful. This thesis investigates the cognitive abnormalities and their electrophysiological correlates across the schizophrenia spectrum in order to identify and validate biomarkers for proof of concept studies of cognitive enhancers. Such studies in milder disorders of the schizophrenia spectrum such as schizotypal personality trait may be a crucial method in identifying new effective compounds, as reviewed in Chapter 3, and tested in Chapter 4. The latter features the results of a large three-centre study which probed the sensitivity of several neuropsychological measures to the schizotypy phenotype, as well as to the effects of amisulpride, risperidone and nicotine. Schizotypal volunteers showed impaired performance only on the more difficult tasks. The most consistent pharmacological finding was that amisulpride tended to improve performance in the high schizotypy group but to impair it in the average schizotypy controls. One interpretation is that the ability of low dose amisulpride to enhance dopamine function in frontal cortex reversed an impairment of dopamine function present in the high schizotypes which is thought to occur in schizophrenia. Chapter 5 explored the methodological question of whether low or average schizotypy individuals should be used as controls in cognitive comparisons versus high schizotypy. The results suggest that low schizotypes have the most intact cognitive performance and are therefore the control group of choice. Chapters 6, 7 and 8 tested the hypothesis that cognitive deficits are part of a larger information processing abnormality in the schizophrenia spectrum. In accordance, both high schizotypy and schizophrenia patients exhibited reduced amplitude of an early visual evoked potential P1 (Chapters 6 and 8, respectively) and disruptions of the underlying evoked neural oscillations (Chapters 7 and 8). The pattern of abnormalities suggested an inefficient top-down modulation of perception in the schizophrenia spectrum. These data argue that cognitive abnormalities and their electrophysiological correlate may be sensitive biomarkers of the core dysconnectivity deficit in schizophrenia. This thesis supports their use in proof of concept studies to foster the development of cognitive enhancers.EThOS - Electronic Theses Online ServiceThe University of ManchesterP1vitalGBUnited Kingdo

Neuropsychological and electrophysiological biomarkers of the schizophrenia spectrum

Schizophrenia is a neuropsychiatric disorder lying at the extreme of a spectrum of disorders that possibly share a common abnormality in neural connectivity. Efforts to reverse the core cognitive manifestations of schizophrenia using drug treatments have so far been unsuccessful. This thesis investigates the cognitive abnormalities and their electrophysiological correlates across the schizophrenia spectrum in order to identify and validate biomarkers for proof of concept studies of cognitive enhancers. Such studies in milder disorders of the schizophrenia spectrum such as schizotypal personality trait may be a crucial method in identifying new effective compounds, as reviewed in Chapter 3, and tested in Chapter 4. The latter features the results of a large three-centre study which probed the sensitivity of several neuropsychological measures to the schizotypy phenotype, as well as to the effects of amisulpride, risperidone and nicotine. Schizotypal volunteers showed impaired performance only on the more difficult tasks. The most consistent pharmacological finding was that amisulpride tended to improve performance in the high schizotypy group but to impair it in the average schizotypy controls. One interpretation is that the ability of low dose amisulpride to enhance dopamine function in frontal cortex reversed an impairment of dopamine function present in the high schizotypes which is thought to occur in schizophrenia. Chapter 5 explored the methodological question of whether low or average schizotypy individuals should be used as controls in cognitive comparisons versus high schizotypy. The results suggest that low schizotypes have the most intact cognitive performance and are therefore the control group of choice. Chapters 6, 7 and 8 tested the hypothesis that cognitive deficits are part of a larger information processing abnormality in the schizophrenia spectrum. In accordance, both high schizotypy and schizophrenia patients exhibited reduced amplitude of an early visual evoked potential P1 (Chapters 6 and 8, respectively) and disruptions of the underlying evoked neural oscillations (Chapters 7 and 8). The pattern of abnormalities suggested an inefficient top-down modulation of perception in the schizophrenia spectrum. These data argue that cognitive abnormalities and their electrophysiological correlate may be sensitive biomarkers of the core dysconnectivity deficit in schizophrenia. This thesis supports their use in proof of concept studies to foster the development of cognitive enhancers.EThOS - Electronic Theses Online ServiceThe University of ManchesterP1vitalGBUnited Kingdo

The UKB envirome of depression

Major depressive disorder is a result of the complex interplay between a large number of environmental and genetic factors but the comprehensive analysis of contributing environmental factors is still an open challenge. The primary aim of this work was to create a Bayesian dependency map of environmental factors of depression, including life stress, social and lifestyle factors, using the UK Biobank data to determine direct dependencies and to characterize mediating or interacting effects of other mental health, metabolic or pain conditions. As a complementary approach, we also investigated the non-linear, synergistic multi-factorial risk of the UKB envirome on depression using deep neural network architectures. Our results showed that a surprisingly small number of core factors mediate the effects of the envirome on lifetime depression: neuroticism, current depressive symptoms, parental depression, body fat, while life stress and household income have weak direct effects. Current depressive symptom showed strong or moderate direct relationships with life stress, pain conditions, falls, age, insomnia, weight change, satisfaction, confiding in someone, exercise, sports and Townsend index. In conclusion, the majority of envirome exerts their effects in a dynamic network via transitive, interactive and synergistic relationships explaining why environmental effects may be obscured in studies which consider them individually

The association between peripheral inflammation, brain glutamate and antipsychotic response in Schizophrenia:Data from the STRATA collaboration

Glutamate and increased inflammation have been separately implicated in the pathophysiology of schizophrenia and the extent of clinical response to antipsychotic treatment. Despite the mechanistic links between pro-inflammatory and glutamatergic pathways, the relationships between peripheral inflammatory markers and brain glutamate in schizophrenia have not yet been investigated. In this study, we tested the hypothesis that peripheral levels of pro-inflammatory cytokines would be positively associated with brain glutamate levels in schizophrenia. Secondary analyses determined whether this relationship differed according to antipsychotic treatment response. The sample consisted of 79 patients with schizophrenia, of whom 40 were rated as antipsychotic responders and 39 as antipsychotic non-responders. Brain glutamate levels were assessed in the anterior cingulate cortex (ACC) and caudate using proton magnetic resonance spectroscopy (1H-MRS) and blood samples were collected for cytokine assay on the same study visit (IL-6, IL-8, IL-10, TNF- α and IFN-γ). Across the whole patient sample, there was a positive relationship between interferon-gamma (IFN-γ) and caudate glutamate levels (r = 0.31, p = 0.02). In the antipsychotic non-responsive group only, there was a positive relationship between interleukin-8 (IL-8) and caudate glutamate (r = 0.46, p = 0.01). These findings provide evidence to link specific peripheral inflammatory markers and caudate glutamate in schizophrenia and may suggest that this relationship is most marked in patients who show a poor response to antipsychotic treatment

Neuroinflammation as measured by positron emission tomography in patients with recent onset and established schizophrenia: implications for immune pathogenesis

From Springer Nature via Jisc Publications RouterHistory: received 2020-01-06, rev-recd 2020-06-09, accepted 2020-06-18, registration 2020-06-19, pub-electronic 2020-06-30, online 2020-06-30, pub-print 2021-09Publication status: PublishedFunder: RCUK | Medical Research Council (MRC); doi: https://doi.org/10.13039/501100000265; Grant(s): MR/K020803/1, MR/K020803/1, MR/K020803/1, MR/K020803/1, MR/K020803/1Abstract: Positron emission tomography (PET) imaging of the 18 kDa translocator protein (TSPO), which is upregulated in activated microglia, is a method for investigating whether immune activation is evident in the brain of adults with schizophrenia. This study aimed to measure TSPO availability in the largest patient group to date, and to compare it between patients with recent onset (ROS) and established (ES) schizophrenia. In total, 20 ROS patients (14 male), 21 ES (13 male), and 21 healthy controls completed the study. Patients were predominantly antipsychotic-medicated. Participants underwent a PET scan using the TSPO-specific radioligand [11C](R)-PK11195. The primary outcome was binding potential (BPND) in the anterior cingulate cortex (ACC). Secondary outcomes were BPND in six other regions. Correlations were investigated between TSPO availability and symptom severity. Data showed that mean BPND was higher in older (ES and controls) compared with younger (ROS and controls) individuals, but did not significantly differ between ROS or ES and their respective age-matched controls (ACC; ANOVA main effect of diagnosis: F1,58 = 0.407, p = 0.526). Compared with controls, BPND was lower in antipsychotic-free (n = 6), but not in medicated, ROS patients. BPND in the ES group was negatively correlated with positive symptoms, and positively correlated with negative symptom score. Our data suggest ageing is associated with higher TSPO but a diagnosis of schizophrenia is not. Rather, subnormal TSPO levels in drug-free recent-onset patients may imply impaired microglial development and/or function, which is counteracted by antipsychotic treatment. The development of novel radioligands for specific immune-mechanisms is needed for further clarification

Cross-sectional study comparing cognitive function in treatment responsive versus treatment non-responsive schizophrenia: evidence from the STRATA study

Background 70%–84% of individuals with antipsychotic treatment resistance show non-response from the first episode. Emerging cross-sectional evidence comparing cognitive profiles in treatment resistant schizophrenia to treatment-responsive schizophrenia has indicated that verbal memory and language functions may be more impaired in treatment resistance. We sought to confirm this finding by comparing cognitive performance between antipsychotic non-responders (NR) and responders (R) using a brief cognitive battery for schizophrenia, with a primary focus on verbal tasks compared against other measures of cognition. Design Cross-sectional. Setting This cross-sectional study recruited antipsychotic treatment R and antipsychotic NR across four UK sites. Cognitive performance was assessed using the Brief Assessment of Cognition in Schizophrenia (BACS). Participants One hundred and six participants aged 18–65 years with a diagnosis of schizophrenia or schizophreniform disorder were recruited according to their treatment response, with 52 NR and 54 R cases. Outcomes Composite and subscale scores of cognitive performance on the BACS. Group (R vs NR) differences in cognitive scores were investigated using univariable and multivariable linear regressions adjusted for age, gender and illness duration. Results Univariable regression models observed no significant differences between R and NR groups on any measure of the BACS, including verbal memory (ß=−1.99, 95% CI −6.63 to 2.66, p=0.398) and verbal fluency (ß=1.23, 95% CI −2.46 to 4.91, p=0.510). This pattern of findings was consistent in multivariable models. Conclusions The lack of group difference in cognition in our sample is likely due to a lack of clinical distinction between our groups. Future investigations should aim to use machine learning methods using longitudinal first episode samples to identify responder subtypes within schizophrenia, and how cognitive factors may interact within this