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

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

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

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

Investigation of relationships between bipolar disorder phenotypes and genome-wide significant loci from PGC2 schizophrenia

Background Schizophrenia (SZ) and Bipolar disorder (BD) show evidence for partial overlap in phenotypic and genetic influences based on family, twins, adoption and Psychiatric Genetic Consortium (PGC) studies. They have lifetime prevalence of about 1% and 2.4%, and heritability estimates of 60-80% and 40-70%, respectively. In the last decade BD has been investigated using dimensional structuring of psychoses based on symptomatic-functional checklists that provides reliable approach to phenotypic assessment. Recent research suggests moving towards developing Phenotype-based Genetic Association Studies. In this approach, patients will only be put into groups consisting of others with symptoms similar to their own. Canonical Correlation Analysis (CCA) is statistical technique designed to identify relationships (usually hidden) between two sets of variables. We use CCA to combine genotypic and phenotypic variables and measure correlation between those sets. This analysis estimates canonical correlation between psychotic symptoms measured using validated item check list (OPCRIT), and genome-wide significant (GWS) loci from PGC2 schizophrenia. Methods For our analysis we used phenotype and genetic data for 5,507 BD cases. Imputation of genetic data was performed with 1000Genomes (Phase 3, 2014) then quality control was applied (INFO>0.8, HWE>1e-6, MAF>0.01). Additional quality control was performed on phenotypic symptom coverage. CCA was employed as implemented in R, using package “CCA” with GWS loci from PGC2 SZ and OPCRIT items. SNPs were standardised and adjusted for 10 population covariates calculated from imputed data using principal component approach prior to CCA. Results Canonical correlation analysis was run on 4422 cases on 89 available GWS PGC2 SZ SNPs or their proxies (with r2>0.6). 60 phenotypic variables were taken from OPCRIT measurements including mood disturbance, biological indices, atypical depression, substance use, psychosis and social functioning. We found no significant canonical correlations indicating absence of hidden sub-clusters at individual symptom level of BD associated with SZ GWS loci. Discussion Our analysis was focused to find correlation from bipolar phenotype by using OPCRIT questionnaire and GWS SZ loci from PGC2. We have shown that there were no significant canonical correlation coefficients suggesting that there is no direct association between SZ associated genetic loci and BP at individual symptom level. CCA is canonical correlation analysis is one of potential of data-driven approaches to identify hidden genotype-phenotype relationships. It provides opportunities to generate and test different hypotheses and understand more about complex architecture of psychiatric disorders. In the next stage we plan to extend our analysis to more fine grained systematic descriptors of BD and test for correlation with genetic profiles from a number of co-morbid disorders, as well as the full range of phenotypic and genetic data that are available

Posttransplant MRD and T-cell chimerism status predict outcomes in patients who received allografts for AML/MDS

Allogeneic stem-cell transplant allows for the delivery of curative graft-versus-leukemia (GVL) in patients with acute myeloid leukemia/myelodysplasia (AML/MDS). Surveillance of T-cell chimerism, measurable residual disease (MRD) and blast HLA-DR expression may inform whether GVL effectiveness is reduced. We report here the prognostic impact of these biomarkers in patients allografted for AML/MDS. One hundred eighty-seven patients from FIGARO, a randomized trial of reduced-intensity conditioning regimens in AML/MDS, were alive and relapse-free at the first MRD time-point and provided monitoring samples for flow cytometric MRD and T-cell chimerism, requested to month+12. Twenty-nine (15.5%) patients had at least 1 MRD-positive result posttransplant. MRD-positivity was associated with reduced overall survival (OS) (hazard ratio [HR], 2.18; P = .0028) as a time-varying Cox variable and remained significant irrespective of pretransplant MRD status in multivariate analyses (P < .001). Ninety-four patients had sequential MRD with T-cell chimerism results at months+3/+6. Patients with full donor T-cell chimerism (FDTC) had an improved OS as compared with patients with mixed donor T-cell chimerism (MDTC) (adjusted HR=0.4; P = .0019). In patients with MDTC (month+3 or +6), MRD-positivity was associated with a decreased 2-year OS (34.3%) vs MRD-negativity (71.4%) (P = .001). In contrast, in the group with FDTC, MRD was infrequent and did not affect the outcome. Among patients with posttransplant MRD-positivity, decreased HLA-DR expression on blasts significantly reduced OS, supporting this as a mechanism for GVL escape. In conclusion, posttransplant MRD is an important predictor of the outcome in patients allografted for AML/MDS and is most informative when combined with T-cell chimerism results, underlining the importance of a GVL effect in AML/MDS