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Knott, S.

Publications and source records attributed to Knott, S..

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SmartCodes : functionalized barcodes that enable targeted retrieval of clonal lineages from a heterogeneous population

Molecular barcoding has provided means to link genotype to phenotype, to individuate cells in single-cell analyses, to enable the tracking of evolving lineages, and to facilitate the analysis of complex mixtures containing phenotypically distinct lineages. To date, all existing approaches enable retrospective associations to be made between characteristics and the lineage harbouring them, but provide no path toward isolating or manipulating those lineages within the complex mixture. Here, we describe a strategy for creating functionalized barcodes that enable straightforward manipulation of lineages within complex populations of cells, either marking and retrieval of selected lineages, or modification of their phenotype within the population, including their elimination. These \"SmartCodes\" rely on a simple CRISPR-based, molecular barcode reader that can switch measurable, or selectable markers, on or off in a binary fashion. While this approach could have broad impact, we envision initial approaches to the study of tumour heterogeneity, focused on issues of tumour progression, metastasis, and drug resistance.

molecular biology

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

ImportanceBipolar 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.\n\nObjectivesTo 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.\n\nDesignCase-control design: using multinomial logistic regression, to estimate differential associations of PRS across categories of cases and controls.\n\nSettings & Participants4399 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.\n\nExposureStandardised 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.\n\nMain outcome measureMultinomial 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).\n\nResultsAcross clinical phenotypes, there was an exposure-response gradient with the strongest PRS association for schizophrenia (RR=1.94, (95% C.1.1.86, 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.1. 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.1.1.36, 1.57)), followed by mood-congruent psychosis (RR= 1.24, (95% C.1. 1.17, 1.33)) and lastly, BD cases with no history of psychosis (RR= 1.09, (95% C.1. 1.04, 1.15)).\n\nConclusionWe 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.

genetics