Age-at-first-admission of schizophrenia, bipolar disorder and major depression: Implications of heterogeneity

Age of onset is an important variable when considering the cause and course of mental illnesses. Given the debate about the relationship between psychotic disorders it would be useful to compare age-at-first-admission for ICD schizophrenia and for affective psychoses when the latter is differentiated into 'major depression' and 'bipolar disorder'. Data on age-at-first-admission for Australian-born individuals diagnosed with schizophrenia (ICD 295) or affective psychosis (ICD 296) were extracted from the Queensland Mental Health Statistics System -- a comprehensive, namelinked mental health register. Because the ICD 9 category 296.1 was used to code what is now called "major depressive episode', this group was differentiated from other 296 categorieswhich were considered bipolar disorders. Those receiving more than one diagnoses within these categories were excluded. All distributions show a wide age range of onset from early adolescence into the seventies and eighties. However the modal age-group for major depression ('60-69' for both sexes) is clearly different from bipolar disorder ('20-29' for males; '30- 39' for females), the latter distribution being more similar to the SCZ distribution (which had a model age-group of '20-29' for both sexes). While these distributions were similar for males and females, there were sex differences in the proportions within each diagnostic group: more males with schizophrenia, and more females with bipolar disorder and with major depression. Our results suggest heterogeneity within the affective psychoses as categorised by ICD 9, with bipolar disorder having an age-at-first-admission distribution more similar to schizophrenia than major depression. The Stanley Foundation supported this project.

Genome scan meta-analysis of schizophrenia and bipolar disorder, part II: Schizophrenia

Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (R-avg) and then weighted for sample size (rootN[affected cases]). A permutation test was used to compute the probability of observing, by chance, each bin's average rank (P-AvgRnk) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (P-ord). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (P-AvgRnk

Slow binocular rivalry in bipolar disorder

Background. The rate of binocular rivalry has been reported to be slower in subjects with bipolar disorder than in controls when tested with drifting, vertical and horizontal gratings of high spatial frequency. Method. Here we assess the rate of binocular rivalry with stationary, vertical and horizontal gratings of low spatial frequency in 30 subjects with bipolar disorder, 30 age- and sex-matched controls, 18 subjects with schizophrenia and 18 subjects with major depression. Along with rivalry rate, the predominance of each of the rivaling images was assessed, as was the distribution of normalized rivalry intervals. Results. The bipolar group demonstrated significantly slower rivalry than the control, schizophrenia and major depression groups. The schizophrenia and major depression groups did not differ significantly from the control group. Predominance values did not differ according to diagnosis and the distribution of normalized rivalry intervals was well described by a gamma function in all groups. Conclusions. The results provide further evidence that binocular rivalry is slow in bipolar disorder and demonstrate that rivalry predominance and the distribution of normalized rivalry intervals are not abnormal in bipolar disorder. It is also shown by comparison with previous work, that high strength stimuli more effectively distinguish bipolar from control subjects than low strength stimuli. The data on schizophrenia and major depression suggest the need for large-scale specificity trials. Further study is also required to assess genetic and pathophysiological factors as well as the potential effects of state, medication, and clinical and biological subtypes.

Cell cycle alterations in biopsied olfactory neuroepithelium in schizophrenia and bipolar I disorder using cell culture and gene expression analyses

We previously demonstrated that olfactory cultures front individuals with schizophrenia had increased cell proliferation compared to Cultures from healthy controls. The aims of this study were to (a) replicate this observation in a new group Of individuals with schizophrenia, (b) examine the specificity of these findings by including individuals with bipolar I disorder and (c) explore gene expression differences that may underlie cell cycle differences in these diseases. Compared to controls (n = 10), there was significantly more mitosis in schizophrenia patient cultures (it = 8) and significantly more cell death in the bipolar I disorder patient cultures (n=8). Microarray data showed alterations to the cell cycle and phosphatidylinositol signalling pathways in schizophrenia and bipolar I disorder, respectively. Whilst caution is required in the interpretation of the array results, the study provides evidence indicating that cell proliferation and cell death in olfactory neuroepithelial cultures is differentially altered in schizophrenia and bipolar disorder. (c) 2005 Elsevier B.V. All rights reserved.

The burden of mental disorders: a comparison of methods between the Australian burden of disease studies and the Global Burden of Disease study

The national and Victorian burden of disease studies in Australia set out to examine critically the methods used in the Global Burden of Disease study to estimate the burden of mental disorders. The main differences include the use of a different set of disability weights allowing estimates in greater detail by level of severity, adjustments for comorbidity between mental disorders, a greater number of menta I disorders measured, and model ling of substance use disorders, anxiety disorders and bipolar disorder as chronic conditions. Uniform age-weighting in the Australian studies produces considerably lower estimates of the burden due to mental disorders in comparison with age-weighted disability-adjusted life years. A lack of follow-up data on people with mental disorders who are identified in cross-sectional surveys poses the greatest challenge in determining the burden of mental disorders more accurately.

Finger and A-B ridge count, and fluctuating asymmetry in psychosis: A catchment area case-control study

Dermatoglyphic measures are of interest to schizophrenia research because they serve as persistent markers of deviant development in foetal life. Several studies have reported alterations in A–B ridge counts, total finger ridge counts and measures related to asymmetry in schizophrenia. The aim of this study was to assess these measures in an Australian catchment area, case-control study. Individuals with psychosisŽns246.were drawn from a catchment-area prevalence study, and well controlsŽns229. were recruited from the same area. Finger and palm prints were taken usingan inkless technique and all dermatoglyphic measures were assessed by a trained rater blind to case status. The dermatoglyphic measures Žfinger ridge count, A–B ridge count, and their derived asymmetry measures. were divided into quartiles based on the distribution of these variables in controls. The main analysis Žlogistic regression controlled for age and sex.examined all psychotic disorders, with planned subgroup analyses comparing controls with Ž1. nonaffective psychosis Žschizophrenia, delusional disorder, schizophreniform psychosis, atypical psychosis.andŽ2. affective psychosis Ždepression with psychosis, bipolar disorder, schizoaffective psychosis.. There were no statistically significant alterations in the odds of havinga psychotic disorder for any of the dermatoglyphic measures. The results did not change when we examined affective and nonaffective psychosis separately. The dermatoglyphic features that distinguish schizophreniar psychosis in other studies were not identified in this Australian study. Regional variations in these findings may provide clues to differential ethnicrgenetic and environmental factors that are associated with schizophrenia. The Stanley Foundation supported this project.

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.

Age-at-first-registration for affective psychosis and schizophrenia

We compared the age-at-first-registration for patients with schizophrenia and affective psychosis in a statewide mental health register. After excluding those receiving (1) a diagnosis of both schizophrenia (ICD-9 295.x) and affective psychosis (ICD-9 296.x), or (2) a diagnosis of ICD-9 296.1 (which can cover major depressive episode), we adjusted the distributions for the age structure of the background general population. We found that all distributions showed a wide age range of onset, with a similar male modal age group of 20-24 for schizophrenia and 25-29 for affective psychosis. The female modal age group was 50-54 for both diagnoses. Although more individuals were diagnosed with schizophrenia (males = 2,434, females = 1,609) than with affective psychosis (males = 670, females = 913), the shape of the two distributions was similar. This finding suggests that factors influencing age-at-first-registration for schizophrenia and affective psychosis may be similar, especially for females.