The application of voxel-based methods to magnetic resonance imaging in the study of psychiatric disorder.

While there are a number of psychiatric disorders as classified by the major international coding systems, however, the application of modem neuroimaging methods has only been utilised on a limited basis with some disorders receiving more research attention than others. Consequently, psychiatric phenotypes that have been relatively understudied are investigated further in this thesis. These disorders correspond to psychiatric disorder in: 22ql 1 deletion syndrome, temporal lobe epilepsy, antisocial personality disorder and Asperger syndrome. Subjects with each of these diagnoses were recruited and then compared to healthy matched controls using the application of novel whole-brain voxel-based analyses to their magnetic resonance imaging data whereby white matter integrity and/or brain tissue volume was assessed in each experimental study of this thesis. In Study 1, young people with 22ql 1 deletion syndrome were found to have significant differences in both white matter microstructure and volume. Additionally, there was preliminary evidence that within 22ql 1 deletion syndrome, some regional differences in fractional anisotropy were associated with allelic variation in COMT and with schizotypy. In Study 2, while significant grey and white matter volume deficits were found in temporal lobe epilepsy with comorbid psychosis, these abnormalities encompassed not only the medial temporal lobe structures but also extended to lateral temporal and extratemporal regions whereby some of the deficits also overlapped with those found in schizophrenia. In Study 3, reduced fractional anisotropy was found in antisocial personality disorder and psychopathy in tracts of interhemispheric, posterior brain and frontal lobe networks. Additionally, fractional anisotropy deficits in the frontal lobe demonstrated a significant negative correlation with psychopathy measures. Finally, in Study 4, adults with Asperger syndrome were specifically recruited and found to not only demonstrate impairments in white matter microstructural integrity in regions relevant to social skills and behaviour but also in more widespread white matter networks

Differences in white matter connectivity between treatment-resistant and treatment-responsive subtypes of schizophrenia

Schizophrenia is a heterogeneous disorder exhibiting variable responsiveness to treatment between individuals. Previous work demonstrated that white matter abnormalities may relate to antipsychotic response but no study to date has examined differences between first-line treatment responders (FLR) and clozapine-eligible individuals receiving first-line antipsychotics. The current study aimed to establish whether differences in white matter structure exist between these two cohorts. Diffusion-weighted images were acquired for 15 clozapine-eligible and 10 FLR participants. Measures of fractional anisotropy (FA), radial diffusivity (RD) and axial diffusivity (AD) were obtained and between-group t-tests interrogating differences in FA were conducted. To investigate the neural basis of a decrease in FA, the significant cluster from FA analysis was masked and used to obtain mean RD and AD measures for that region. Those who were clozapine-eligible had significantly lower FA in the body of the corpus callosum (p < 0.05), associated with a significant increase in mean RD compared with FLR (p < 0.001). No difference in mean AD was observed for this region. These data reveal differences in diffusion measures between FLR and those eligible for clozapine and suggest that lower FA and greater RD in the corpus callosum could exist as a biomarker of treatment resistance in people with schizophrenia

Disrupted white matter integrity in treatment-resistant schizophrenia

Treatment response in schizophrenia is heterogeneous and has been posited to divide into three distinct subcategories: treatment-responsive (first-line responders; FLR), treatment-resistant (TRS, responding to clozapine), and ultra-treatment-resistant schizophrenia (UTRS, requiring augmented antipsychotic therapy). Previous work suggests that white matter abnormalities drive antipsychotic resistance but little work has been carried out to identify differences between those with TRS and those with UTRS. The current study aimed to establish whether differences in white matter structure are present across both treatment-resistant subtypes of schizophrenia or if UTRS is distinct from TRS. Diffusion-weighted images were acquired for 18 individuals with TRS, 14 with UTRS, 18 FLR and 20 healthy controls. Measures of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and parallel diffusivity (PD) were obtained using tract-based spatial statistics. Analysis of variance (ANOVA) and post-hoc between-groups t-tests interrogating differences were conducted for each white matter measure. Those with TRS had lower FA than healthy controls across widespread regions of the brain, including the superior longitudinal fasciculus, corpus callosum, thalamic radiation, corticospinal tract, internal capsule, corona radiata and fronto-occipital fasciculus (p<.05 FWE-corrected). Lower FA was also observed in those with TRS compared with UTRS in the superior longitudinal fasciculus (p<.05 FWE-corrected). However, post-hoc tests failed to survive corrections for multiple comparisons across the 12 post-hoc contrasts. No differences in MD, PD or RD were observed between groups. These data suggest that TRS is distinct from UTRS and that lower FA could act as a biomarker of treatment resistance in people with schizophrenia

Aberrant white matter microstructure in treatment-resistant schizophrenia

Treatment response in schizophrenia divides into three subcategories: treatment-responsive (first-line responders; FLR), treatment-resistant (TRS), and ultra-treatment-resistant schizophrenia (UTRS). White matter abnormalities could drive antipsychotic resistance but little work has investigated differences between TRS and UTRS. The current study aimed to establish whether differences in white matter structure are present across both treatment-resistant subtypes or if UTRS is distinct from TRS. Diffusion-weighted images were acquired for 18 individuals with TRS, 14 with UTRS, 18 FLR and 20 healthy controls. Measures of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD) were obtained using tract-based spatial statistics. Analysis of variance and post-hoc t-tests were conducted for each measure. Those with TRS had lower FA than healthy controls in superior longitudinal fasciculus, corpus callosum, thalamic radiation, corticospinal tract, internal capsule, corona radiata and fronto-occipital fasciculus (p<.05 FWE-corrected). Lower FA was also observed in TRS compared with UTRS in the superior longitudinal fasciculus (p<.05 FWE-corrected). No post-hoc tests survived corrections for multiple comparisons and no differences in MD, AD or RD were observed. These data suggest that microstructural deficits in white matter could contribute to TRS but suggest that other mechanisms may be more relevant for UTRS

White matter microstructure in 22q11 deletion syndrome: a pilot diffusion tensor imaging and voxel-based morphometry study of children and adolescents

Young people with 22q11 Deletion Syndrome (22q11DS) are at substantial risk for developing psychosis and have significant differences in white matter (WM) volume. However, there are few in vivo studies of both WM microstructural integrity (as measured using Diffusion Tensor (DT)-MRI) and WM volume in the same individual. We used DT-MRI and structural MRI (sMRI) with voxel based morphometry (VBM) to compare, respectively, the fractional anisotropy (FA) and WM volume of 11 children and adolescents with 22q11DS and 12 controls. Also, within 22q11DS we related differences in WM to severity of schizotypy, and polymorphism of the catechol-O-methyltransferase (COMT) gene. People with 22q11DS had significantly lower FA in inter-hemispheric and brainstem and frontal, parietal and temporal lobe regions after covarying for IQ. Significant WM volumetric increases were found in the internal capsule, anterior brainstem and frontal and occipital lobes. There was a significant negative correlation between increased schizotypy scores and reduced WM FA in the right posterior limb of internal capsule and the right body and left splenium of corpus callosum. Finally, the Val allele of COMT was associated with a significant reduction in both FA and volume of WM in the frontal lobes, cingulum and corpus callosum. Young people with 22q11DS have significant differences in both WM microstructure and volume. Also, there is preliminary evidence that within 22q11DS, some regional differences in FA are associated with allelic variation in COMT and may perhaps also be associated with schizotypy

Children’s and adolescents’ rising animal-source food intakes in 1990–2018 were impacted by age, region, parental education and urbanicity

Animal-source foods (ASF) provide nutrition for children and adolescents’ physical and cognitive development. Here, we use data from the Global Dietary Database and Bayesian hierarchical models to quantify global, regional and national ASF intakes between 1990 and 2018 by age group across 185 countries, representing 93% of the world’s child population. Mean ASF intake was 1.9 servings per day, representing 16% of children consuming at least three daily servings. Intake was similar between boys and girls, but higher among urban children with educated parents. Consumption varied by age from 0.6 at <1 year to 2.5 servings per day at 15–19 years. Between 1990 and 2018, mean ASF intake increased by 0.5 servings per week, with increases in all regions except sub-Saharan Africa. In 2018, total ASF consumption was highest in Russia, Brazil, Mexico and Turkey, and lowest in Uganda, India, Kenya and Bangladesh. These findings can inform policy to address malnutrition through targeted ASF consumption programmes.publishedVersio

Incident type 2 diabetes attributable to suboptimal diet in 184 countries

The global burden of diet-attributable type 2 diabetes (T2D) is not well established. This risk assessment model estimated T2D incidence among adults attributable to direct and body weight-mediated effects of 11 dietary factors in 184 countries in 1990 and 2018. In 2018, suboptimal intake of these dietary factors was estimated to be attributable to 14.1 million (95% uncertainty interval (UI), 13.8–14.4 million) incident T2D cases, representing 70.3% (68.8–71.8%) of new cases globally. Largest T2D burdens were attributable to insufficient whole-grain intake (26.1% (25.0–27.1%)), excess refined rice and wheat intake (24.6% (22.3–27.2%)) and excess processed meat intake (20.3% (18.3–23.5%)). Across regions, highest proportional burdens were in central and eastern Europe and central Asia (85.6% (83.4–87.7%)) and Latin America and the Caribbean (81.8% (80.1–83.4%)); and lowest proportional burdens were in South Asia (55.4% (52.1–60.7%)). Proportions of diet-attributable T2D were generally larger in men than in women and were inversely correlated with age. Diet-attributable T2D was generally larger among urban versus rural residents and higher versus lower educated individuals, except in high-income countries, central and eastern Europe and central Asia, where burdens were larger in rural residents and in lower educated individuals. Compared with 1990, global diet-attributable T2D increased by 2.6 absolute percentage points (8.6 million more cases) in 2018, with variation in these trends by world region and dietary factor. These findings inform nutritional priorities and clinical and public health planning to improve dietary quality and reduce T2D globally.publishedVersio

Late-Life Suicide in Terminal Cancer:A Rational Act or Underdiagnosed Depression?

Context. Previous studies have reported significantly elevated standardized mortality rates in older people with cancer. Terminally ill people represent a unique group where suicide may be considered as rational. Objectives. The aims of this study are to compare the sociodemographic and clinical characteristics of older people with and without terminal cancer who died by suicide and analyze the suicide motives of those with terminal cancer to determine whether they represent rational suicide. Methods. The New Zealand Coronial Services provided records of all older people (aged 65 years and older) who died by suicide between July 2007 and December 2012. Sociodemographic and clinical data were extracted from the records. Using the characteristics for defining rational suicide, we determined whether the motives in terminal cancer cases represented rational suicide. Results. Of the 214 suicide cases, 23 (10.7%) older people were diagnosed with a terminal cancer. Univariate analysis found that older people with terminal cancer who died by suicide were less likely to have a diagnosis of depression (8.7% vs. 46.6%; P = 0.001) or previous contact with mental health services (4.5% vs. 35.0%; P = 0.004) than those without terminal cancer. About 82.6% of the terminal cancer cases had a motivational basis that would be understandable to uninvolved observers. Conclusion. A high proportion of those with terminal cancer had motives suggestive of rational suicide. Future studies are needed to clarify whether the low rate of depression is secondary to underdiagnosis of depression or people with terminal cancer choosing to end their life as a rational act to alleviate suffering. (C) 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved

Using Acoustic Speech Patterns From Smartphones to Investigate Mood Disorders: Scoping Review

BackgroundMood disorders are commonly underrecognized and undertreated, as diagnosis is reliant on self-reporting and clinical assessments that are often not timely. Speech characteristics of those with mood disorders differs from healthy individuals. With the wide use of smartphones, and the emergence of machine learning approaches, smartphones can be used to monitor speech patterns to help the diagnosis and monitoring of mood disorders. ObjectiveThe aim of this review is to synthesize research on using speech patterns from smartphones to diagnose and monitor mood disorders. MethodsLiterature searches of major databases, Medline, PsycInfo, EMBASE, and CINAHL, initially identified 832 relevant articles using the search terms “mood disorders”, “smartphone”, “voice analysis”, and their variants. Only 13 studies met inclusion criteria: use of a smartphone for capturing voice data, focus on diagnosing or monitoring a mood disorder(s), clinical populations recruited prospectively, and in the English language only. Articles were assessed by 2 reviewers, and data extracted included data type, classifiers used, methods of capture, and study results. Studies were analyzed using a narrative synthesis approach. ResultsStudies showed that voice data alone had reasonable accuracy in predicting mood states and mood fluctuations based on objectively monitored speech patterns. While a fusion of different sensor modalities revealed the highest accuracy (97.4%), nearly 80% of included studies were pilot trials or feasibility studies without control groups and had small sample sizes ranging from 1 to 73 participants. Studies were also carried out over short or varying timeframes and had significant heterogeneity of methods in terms of the types of audio data captured, environmental contexts, classifiers, and measures to control for privacy and ambient noise. ConclusionsApproaches that allow smartphone-based monitoring of speech patterns in mood disorders are rapidly growing. The current body of evidence supports the value of speech patterns to monitor, classify, and predict mood states in real time. However, many challenges remain around the robustness, cost-effectiveness, and acceptability of such an approach and further work is required to build on current research and reduce heterogeneity of methodologies as well as clinical evaluation of the benefits and risks of such approaches