Multivariate neuroanatomical classification of cognitive subtypes in schizophrenia: A support vector machine learning approach

AbstractHeterogeneity in the structural brain abnormalities associated with schizophrenia has made identification of reliable neuroanatomical markers of the disease difficult. The use of more homogenous clinical phenotypes may improve the accuracy of predicting psychotic disorder/s on the basis of observable brain disturbances. Here we investigate the utility of cognitive subtypes of schizophrenia – ‘cognitive deficit’ and ‘cognitively spared’ – in determining whether multivariate patterns of volumetric brain differences can accurately discriminate these clinical subtypes from healthy controls, and from each other. We applied support vector machine classification to grey- and white-matter volume data from 126 schizophrenia patients previously allocated to the cognitive spared subtype, 74 cognitive deficit schizophrenia patients, and 134 healthy controls. Using this method, cognitive subtypes were distinguished from healthy controls with up to 72% accuracy. Cross-validation analyses between subtypes achieved an accuracy of 71%, suggesting that some common neuroanatomical patterns distinguish both subtypes from healthy controls. Notably, cognitive subtypes were best distinguished from one another when the sample was stratified by sex prior to classification analysis: cognitive subtype classification accuracy was relatively low (<60%) without stratification, and increased to 83% for females with sex stratification. Distinct neuroanatomical patterns predicted cognitive subtype status in each sex: sex-specific multivariate patterns did not predict cognitive subtype status in the other sex above chance, and weight map analyses demonstrated negative correlations between the spatial patterns of weights underlying classification for each sex. These results suggest that in typical mixed-sex samples of schizophrenia patients, the volumetric brain differences between cognitive subtypes are relatively minor in contrast to the large common disease-associated changes. Volumetric differences that distinguish between cognitive subtypes on a case-by-case basis appear to occur in a sex-specific manner that is consistent with previous evidence of disrupted relationships between brain structure and cognition in male, but not female, schizophrenia patients. Consideration of sex-specific differences in brain organization is thus likely to assist future attempts to distinguish subgroups of schizophrenia patients on the basis of neuroanatomical features

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe

Systematic Meta-Analysis of Insula Volume in Schizophrenia

Background Volume reduction in insular cortex may constitute an important neuropathology in schizophrenia. We provide the first meta-analysis of studies that conducted region-of-interest analyses of the magnitude of effect and pattern of insula volume reduction in schizophrenia compared with healthy control subjects. Methods Included studies examined insula volume in schizophrenia relative to healthy control subjects. Studies were located via electronic database searches and hand searching. Study selection, data extraction, and quality assessment were completed by two independent reviewers. Hedge's g effect sizes were calculated using Comprehensive Meta-Analysis (v.2) to quantify volumetric differences between people with and without schizophrenia, accounting for moderating influences of age, sex, illness duration, medication, whole brain volume, and potential differences in hemispheric and anatomical subregions. Results Random-effects analysis showed reductions of bilateral insula (n = 945, g = −.446, 95% confidence interval −.639 to −.252, p = .00001), with moderate heterogeneity apparent (I2 = 76%). This effect was consistent across left and right insula and not influenced by illness stage or sex. Additional analyses revealed larger reductions of anterior (n = 605, g = −.643, p Conclusions This meta-analysis indicates medium-sized reduction of insula volume in schizophrenia, of greatest magnitude in the anterior subregion. Cellular distinctions across anterior and posterior insula may contribute to understanding the neuropathology and functional significance of the observed volumetric differences

Meta-analysis of insula grey matter volume in schizophrenia

There is increasing interest in the insula as a key region of neuropathology in schizophrenia. Several voxel-based meta-analyses of magnetic resonance imaging (MRI) studies have highlighted insula grey matter deficits in people with schizophrenia. However, volumetric studies targeting insula grey matter volume, to date, do not give a clear picture of insula morphometry. We undertook the first systematic review with meta- analysis of studies examining insula volume in schizophrenia compared to healthy controls

Systematic meta-analysis of childhood social withdrawal in schizophrenia, and comparison with data from at-risk children aged 9-14 years

Social withdrawal is a robust childhood risk factor for later schizophrenia. The aims of this paper were to assess the evidence for childhood social withdrawal among adults with schizophrenia and, comparatively, in children aged 9–14 years who are putatively at-risk of developing schizophrenia. We conducted a meta-analysis, including cohort and case-control studies reporting social withdrawal measured by the Child Behavior Checklist (CBCL) in adults with schizophrenia vs. controls. Further, an experimental study compared CBCL withdrawal scores from typically-developing children with scores from two groups of putatively at-risk children: (i) children displaying a triad of replicated antecedents for schizophrenia, and (ii) children with at least one first- or second-degree relative with schizophrenia or schizoaffective disorder. Six studies met inclusion criteria for the meta-analysis (N = 3828), which demonstrated a large effect of increased childhood social withdrawal in adults with schizophrenia (standardized mean difference [SMD] score = 1.035, 95% CI = 0.304–1.766, p = 0.006), with no indication of publication bias, but considerable heterogeneity (I2 = 91%). Results from the experimental study also indicated a large effect of increased social withdrawal in children displaying the antecedent triad (SMD = 0.743, p = 0.001), and a weaker effect in children with a family history of schizophrenia (SMD = 0.442, p = 0.051). Childhood social withdrawal may constitute a vulnerability marker for schizophrenia in the presence of other antecedents and/or genetic risk factors for schizophrenia

Psychophysical Impact and Optical and Morphological Characteristics of Symptomatic Non-Advanced Cataract.

Purpose To investigate whetherpsychophysical, morphological, and/or opticalcharacteristics of symptomatic non-advancedcataract are complementary to, or moreappropriate than, visual acuity (VA) for thepurposes of recording visual data that reflectsubjective visual difficulty in patients withcataract that exhibit relative sparing of highcontrast acuity (0.4 logarithm of minimal angleof resolution (logMAR) scale or better)

Policy and service development implications of the second Australian National Survey of High Impact Psychosis (SHIP)

Objective: We consider insights from the second Australian National Survey of High Impact Psychosis (2010) in order to identify the key policy and service development implications

Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index

A large number of genetic loci are associated with adult body mass index. However, the genetics of childhood body mass index are largely unknown. We performed a meta-analysis of genome-wide association studies of childhood body mass index, using sex- and age-adjusted standard deviation scores. We included 35 668 children from 20 studies in the discovery phase and 11 873 children from 13 studies in the replication phase. In total, 15 loci reached genome-wide significance (P-value < 5 × 10(-8)) in the joint discovery and replication analysis, of which 12 are previously identified loci in or close to ADCY3, GNPDA2, TMEM18, SEC16B, FAIM2, FTO, TFAP2B, TNNI3K, MC4R, GPR61, LMX1B and OLFM4 associated with adult body mass index or childhood obesity. We identified three novel loci: rs13253111 near ELP3, rs8092503 near RAB27B and rs13387838 near ADAM23. Per additional risk allele, body mass index increased 0.04 Standard Deviation Score (SDS) [Standard Error (SE) 0.007], 0.05 SDS (SE 0.008) and 0.14 SDS (SE 0.025), for rs13253111, rs8092503 and rs13387838, respectively. A genetic risk score combining all 15 SNPs showed that each additional average risk allele was associated with a 0.073 SDS (SE 0.011, P-value = 3.12 × 10(-10)) increase in childhood body mass index in a population of 1955 children. This risk score explained 2% of the variance in childhood body mass index. This study highlights the shared genetic background between childhood and adult body mass index and adds three novel loci. These loci likely represent age-related differences in strength of the associations with body mass index