Prevalence and correlates of psychotic experiences amongst children of depressed parents

Psychotic experiences in young people are substantially more common than psychotic disorders, and are associated with distress and functional impairment. Family history of depression as well as of schizophrenia increases risk for psychotic experiences, but the prevalence of such experiences and their clinical relevance in offspring of depressed parents is unknown. Our objectives were to explore i) the prevalence of psychotic experiences amongst offspring of parents with recurrent unipolar depression and ii) the relationship between psychotic experiences and other psychopathology. Data were drawn from the ‘Early Prediction of Adolescent Depression’ longitudinal study of high-risk offspring (aged 9–17 years at baseline) of 337 parents with recurrent depression. Three assessments were conducted over four years. Psychopathology was assessed using the Child and Adolescent Psychiatric Assessment. Seventy-eight percent of families (n=262) had complete data on psychotic experiences at each of the three time points. During the study, 8.4% (n=22; 95% CI 5.0%, 11.8%) of offspring reported psychotic experiences on at least one occasion, and these were associated with psychiatric disorder, specifically mood and disruptive disorders, and suicidal thoughts/behaviour. Psychotic experiences amongst offspring of depressed parents index a range of psychopathology. Further research is needed to examine their clinical significance and long-term consequences

A dynamic network approach for the study of human phenotypes

The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have; (2) the progression of disease along the links of the network is different for patients of different genders and ethnicities; (3) patients diagnosed with diseases which are more highly connected in the PDN tend to die sooner than those affected by less connected diseases; and (4) diseases that tend to be preceded by others in the PDN tend to be more connected than diseases that precede other illnesses, and are associated with higher degrees of mortality. Our findings show that disease progression can be represented and studied using network methods, offering the potential to enhance our understanding of the origin and evolution of human diseases. The dataset introduced here, released concurrently with this publication, represents the largest relational phenotypic resource publicly available to the research community.Comment: 28 pages (double space), 6 figure

De novo CNVs in bipolar affective disorder and schizophrenia

An increased rate of de novo copy number variants (CNVs) has been found in schizophrenia (SZ), autism and developmental delay. An increased rate has also been reported in bipolar affective disorder (BD). Here, in a larger BD sample, we aimed to replicate these findings and compare de novo CNVs between SZ and BD. We used Illumina microarrays to genotype 368 BD probands, 76 SZ probands and all their parents. Copy number variants were called by PennCNV and filtered for frequency (10 kb). Putative de novo CNVs were validated with the z-score algorithm, manual inspection of log R ratios (LRR) and qPCR probes. We found 15 de novo CNVs in BD (4.1% rate) and 6 in SZ (7.9% rate). Combining results with previous studies and using a cut-off of >100 kb, the rate of de novo CNVs in BD was intermediate between controls and SZ: 1.5% in controls, 2.2% in BD and 4.3% in SZ. Only the differences between SZ and BD and SZ and controls were significant. The median size of de novo CNVs in BD (448 kb) was also intermediate between SZ (613 kb) and controls (338 kb), but only the comparison between SZ and controls was significant. Only one de novo CNV in BD was in a confirmed SZ locus (16p11.2). Sporadic or early onset cases were not more likely to have de novo CNVs. We conclude that de novo CNVs play a smaller role in BD compared with SZ. Patients with a positive family history can also harbour de novo mutations

Rydberg Ensembles for Quantum Networking

Rydberg ensembles, atomic clouds with one or more atoms excited to a Rydberg state, have proven to be a good platform for the study of photon-photon interactions. This is due to the nonlinearities they exhibit at the single photon level arising from Rydberg-Rydberg interactions. As a result, they have shown promise for use in a multitude of applications, among them quantum networking. In this thesis I describe the construction and operation of an apparatus for the purpose of cooling, trapping and probing Rydberg ensemble physics in a cloud of ${}^{87}\textrm{Rb}$ atoms. In addition, I describe a pair of projects undertaken with the apparatus. In the first, I report our demonstration of a Rydberg ensemble based on-demand single photon source. Here, we make use of Rydberg blockade to allow us to prepare a single collective Rydberg excitation in the cloud. The spin wave excitation is then retrieved by coherently mapping it onto a propagating photon. Our source is highly pure and efficient, while producing narrow bandwidth and indistinguishable photons. Such sources are important devices for the purposes of quantum networking, computation and metrology. Following from this, I describe a collaborative project where we show time resolved Hong-Ou-Mandel interference between photons produced by our Rydberg ensemble source, and a collaborators source based on a single trapped barium ion. This demonstration is a critical step in the entanglement, and hybrid quantum networking, of these two disparate systems

Psychosis and the level of mood incongruence in Bipolar Disorder are related to genetic liability for Schizophrenia

Abstract Importance Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes/mechanisms. Objectives To investigate the relationship between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRS) and psychotic presentations of BD, using clinical descriptions which consider both occurrence and level of mood-incongruent psychotic features. Design Case-control design: using multinomial logistic regression, to estimate differential associations of PRS across categories of cases and controls. Settings & Participants 4399 BDcases, mean [sd] age-at-interview 46[12] years, of which 2966 were woman (67%) from the BD Research Network (BDRN) were included in the final analyses, with data for 4976 schizophrenia cases and 9012 controls from the Type-1 diabetes genetics consortium and Generation Scotland included for comparison. Exposure Standardised PRS, calculated using alleles with an association p-value threshold < 0.05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, adjusted for the first 10 population principal components and genotyping-platform. Main outcome measure Multinomial logit models estimated PRS associations with BD stratified by (1) Research Diagnostic Criteria (RDC) BD subtypes (2) Lifetime occurrence of psychosis.(3) Lifetime mood-incongruent psychotic features and (4) ordinal logistic regression examined PRS associations across levels of mood-incongruence. Ratings were derived from the Schedule for Clinical Assessment in Neuropsychiatry interview (SCAN) and the Bipolar Affective Disorder Dimension Scale (BADDS). Results Across clinical phenotypes, there was an exposure-response gradient with the strongest PRS association for schizophrenia (RR=1.94, (95% C.I. 1.86, 2.01)), then schizoaffective BD (RR=1.37, (95% C.I. 1.22, 1.54)), BD I (RR= 1.30, (95% C.I. 1.24, 1.36)) and BD II (RR=1.04, (95% C.I. 0.97, 1.11)). Within BD cases, there was an effect gradient, indexed by the nature of psychosis, with prominent mood-incongruent psychotic features having the strongest association (RR=1.46, (95% C.I. 1.36, 1.57)), followed by mood-congruent psychosis (RR= 1.24, (95% C.I. 1.17, 1.33)) and lastly, BD cases with no history of psychosis (RR=1.09, (95% C.I. 1.04, 1.15)). Conclusion We show for the first time a polygenic-risk gradient, across schizophrenia and bipolar disorder, indexed by the occurrence and level of mood-incongruent psychotic symptoms

Investigation of the genetic association between quantitative measures of psychosis and schizophrenia:A polygenic risk score analysis

The presence of subclinical levels of psychosis in the general population may imply that schizophrenia is the extreme expression of more or less continuously distributed traits in the population. In a previous study, we identified five quantitative measures of schizophrenia (positive, negative, disorganisation, mania, and depression scores). The aim of this study is to examine the association between a direct measure of genetic risk of schizophrenia and the five quantitative measures of psychosis. Estimates of the log of the odds ratios of case/control allelic association tests were obtained from the Psychiatric GWAS Consortium (PGC) (minus our sample) which included genome-wide genotype data of 8,690 schizophrenia cases and 11,831 controls. These data were used to calculate genetic risk scores in 314 schizophrenia cases and 148 controls from the Netherlands for whom genotype data and quantitative symptom scores were available. The genetic risk score of schizophrenia was significantly associated with case-control status (p<0.0001). In the case-control sample, the five psychosis dimensions were found to be significantly associated with genetic risk scores; the correlations ranged between.15 and.27 (all p<.001). However, these correlations were not significant in schizophrenia cases or controls separately. While this study confirms the presence of a genetic risk for schizophrenia as categorical diagnostic trait, we did not find evidence for the genetic risk underlying quantitative schizophrenia symptom dimensions. This does not necessarily imply that a genetic basis is nonexistent, but does suggest that it is distinct from the polygenic risk score for schizophrenia

Genome-wide association study of borderline personality disorder reveals genetic overlap with the bipolar disorder, schizophrenia and major depression

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of Bipolar Disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was: (i) to detect genes and gene-sets involved in BOR; and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, Major Depression (MDD) and Schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests,and gene-set-analyses were performed in 998 BOR patients and 1,545 controls. LD score regression was used to detect genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Genebased analysis yielded two significant genes: DPYD (p=4.42x10-7) and PKP4 (p=8.67x10-7); and gene-set-analysis yielded a significant finding for exocytosis (GO:0006887, pFDR=0.019). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [p=2.99x10-3]), SCZ (rg=0.34 [p=4.37x10-5]), and MDD (rg=0.57 [p=1.04x10-3]). Our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies

Genome-wide association studies: a primer

There have been nearly 400 genome-wide association studies (GWAS) published since 2005. The GWAS approach has been exceptionally successful in identifying common genetic variants that predispose to a variety of complex human diseases and biochemical and anthropometric traits. Although this approach is relatively new, there are many excellent reviews of different aspects of the GWAS method. Here, we provide a primer, an annotated overview of the GWAS method with particular reference to psychiatric genetics. We dissect the GWAS methodology into its components and provide a brief description with citations and links to reviews that cover the topic in detail

Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping

To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1–2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks