Assuntos
Doença de Alzheimer , Glicoproteínas de Membrana , Receptores Imunológicos , Idoso , Feminino , Humanos , Masculino , Doença de Alzheimer/etnologia , Doença de Alzheimer/genética , Doença de Alzheimer/metabolismo , Apolipoproteínas E/metabolismo , LDL-Colesterol/metabolismo , Clusterina/metabolismo , Predisposição Genética para Doença/genética , Homozigoto , Glicoproteínas de Membrana/genética , Glicoproteínas de Membrana/metabolismo , Mutação de Sentido Incorreto , Receptores Imunológicos/genética , Receptores Imunológicos/metabolismoRESUMO
Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.
Assuntos
Antipsicóticos , Bancos de Espécimes Biológicos , Herança Multifatorial , Polimedicação , Sistema de Registros , Esquizofrenia , Humanos , Antipsicóticos/administração & dosagem , Antipsicóticos/uso terapêutico , Masculino , Feminino , Esquizofrenia/tratamento farmacológico , Esquizofrenia/genética , Pessoa de Meia-Idade , Adulto , Transtornos Psicóticos/tratamento farmacológico , Transtornos Psicóticos/genética , Estudos de Coortes , IdosoRESUMO
Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants. We performed genome-wide association meta-analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified two novel loci associated with non-response to antidepressants and showed significant polygenic prediction in independent samples. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.