RESUMO
The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.
Assuntos
Transtornos Psicóticos , Esquizofrenia , Cognição , Variações do Número de Cópias de DNA/genética , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla , Humanos , Transtornos Psicóticos/genética , Esquizofrenia/genéticaRESUMO
BACKGROUND: There is increasing evidence for shared genetic susceptibility between schizophrenia and bipolar disorder. Although genetic variants only convey subtle increases in risk individually, their combination into a polygenic risk score constitutes a strong disease predictor.AimsTo investigate whether schizophrenia and bipolar disorder polygenic risk scores can distinguish people with broadly defined psychosis and their unaffected relatives from controls. METHOD: Using the latest Psychiatric Genomics Consortium data, we calculated schizophrenia and bipolar disorder polygenic risk scores for 1168 people with psychosis, 552 unaffected relatives and 1472 controls. RESULTS: Patients with broadly defined psychosis had dramatic increases in schizophrenia and bipolar polygenic risk scores, as did their relatives, albeit to a lesser degree. However, the accuracy of predictive models was modest. CONCLUSIONS: Although polygenic risk scores are not ready for clinical use, it is hoped that as they are refined they could help towards risk reduction advice and early interventions for psychosis.Declaration of interestR.M.M. has received honoraria for lectures from Janssen, Lundbeck, Lilly, Otsuka and Sunovian.
Assuntos
Transtorno Bipolar/genética , Transtornos Psicóticos/genética , Esquizofrenia/genética , Adulto , Austrália , Estudos de Casos e Controles , Europa (Continente) , Feminino , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Herança Multifatorial , Polimorfismo de Nucleotídeo Único , Fatores de Risco , Adulto JovemRESUMO
Electroencephalography (EEG) is a widely used tool in neuropsychiatry research. The most used measurements in EEG are the amplitude and latency of the cortical electrophysiological activity in response to stimulus, known as evoked potentials. Besides potentials, time/frequency analysis is also used to obtain information on global fluctuations of the recordings, which evoked potentials do not provide. Time/frequency analysis results in different values known as derived measures. In this work, a brief introduction to evoked potentials and time/frequency analyses in schizophrenia is given, focusing on P300, noise power, and spectral entropy. Finally, a detailed description is given on how to obtain EEG recordings, evoked potentials, and derived measures.