Stanley Zammit

Bio: Stanley Zammit is an academic researcher from University of Bristol. The author has contributed to research in topics: Longitudinal study & Population. The author has an hindex of 63, co-authored 256 publications receiving 18021 citations. Previous affiliations of Stanley Zammit include Cardiff University & University of Wales.

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

Abstract: Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Identification of loci associated with schizophrenia by genome-wide association and follow-up

Abstract: We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10(-5) in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 x 10(-4)), and the overall pattern of replication was unlikely to occur by chance (P = 9 x 10(-8)). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 x 10(-7)) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 x 10(-9)).

Self reported cannabis use as a risk factor for schizophrenia in Swedish conscripts of 1969: historical cohort study

Abstract: Objectives: An association between use of cannabis in adolescence and subsequent risk of schizophrenia was previously reported in a follow up of Swedish conscripts. Arguments were raised that this association may be due to use of drugs other than cannabis and that personality traits may have confounded results. We performed a further analysis of this cohort to address these uncertainties while extending the follow up period to identify additional cases. Design: Historical cohort study. Setting: 1969-70 survey of Swedish conscripts (>97% of the country's male population aged 18-20). Participants: 50 087 subjects: data were available on self reported use of cannabis and other drugs, and on several social and psychological characteristics. Main outcome measures: Admissions to hospital for ICD-8/9 schizophrenia and other psychoses, as determined by record linkage. Results: Cannabis was associated with an increased risk of developing schizophrenia in a dose dependent fashion both for subjects who had ever used cannabis (adjusted odds ratio for linear trend of increasing frequency 1.2, 95% confidence interval 1.1 to 1.4, P 50 times was 6.7 (2.1 to 21.7) in the cannabis only group. Similar results were obtained when analysis was restricted to subjects developing schizophrenia after five years after conscription, to exclude prodromal cases. Conclusions: Cannabis use is associated with an increased risk of developing schizophrenia, consistent with a causal relation. This association is not explained by use of other psychoactive drugs or personality traits relating to social integration. #### What is already known about this topic What is already known about this topic Use of cannabis has been associated with an increased risk of developing schizophrenia Alternative explanations for this association include confounding by personality or by use of other drugs such as amphetamines, and use of cannabis as a form of self medication secondary to the disorder #### What this study adds What this study adds Self reported cannabis use is associated with an increased risk of subsequently developing schizophrenia, consistent with a causal relation This association is not explained by sociability personality traits, or by use of amphetamines or other drugs Self medication with cannabis is an unlikely explanation for the association observed

Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Abstract: Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

mice: Multivariate Imputation by Chained Equations in R

Abstract: The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice, which extends the functionality of mice 1.0 in several ways. In mice, the analysis of imputed data is made completely general, whereas the range of models under which pooling works is substantially extended. mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs. Imputation of categorical data is improved in order to bypass problems caused by perfect prediction. Special attention is paid to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. mice can be downloaded from the Comprehensive R Archive Network. This article provides a hands-on, stepwise approach to solve applied incomplete data problems.

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Biological insights from 108 schizophrenia-associated genetic loci

Abstract: Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

Medscape

Abstract: Secret History: Return of the Black Death Channel 4, 7-8pm In 1348 the Black Death swept through London, killing people within days of the appearance of their first symptoms. Exactly how many died, and why, has long been a mystery. This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale. And they ask, what might be coming next?