Neurocognitive Heterogeneity in Patients with Psychosis _ A Dimensional Approach

精神病患者的神经认知异质性_维度方法

• 批准号: 8634973
• 负责人: Katherine Elizabeth Burdick
• 金额: --
• 依托单位: JAMES J PETERS VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8634973
• 关键词: Acute; Address; Adult; Affective; Affective Symptoms; Alcohol or Other Drugs use; Architecture; Bipolar Disorder; Blood specimen; Brain; Candidate Disease Gene; Childhood; Clinical; Clinical Data; Cluster Analysis; Cognitive; Cognitive deficits; Comorbidity; DNA; DSM-IV; Data; Diagnosis; Diagnostic; Dimensions; Disease; Disease remission; Economic Burden; Environmental Risk Factor; Etiology; Family; Functional disorder; Future; Genes; Genetic; Genome; Genomics; Genotype; Health system; Heterogeneity; Impaired cognition; Impairment; Individual; Medical; Modeling; Molecular; Molecular Genetics; Molecular Target; Neurocognition; Neurocognitive; Occupational; Outcome; Pathway interactions; Patient Care; Patients; Pattern; Performance; Phenotype; Play; Psychotic Disorders; Quality of life; Recording of previous events; Risk; Sampling; Schizophrenia; Sleep; Structure; Subgroup; Symptoms; System; Testing; Trauma; Variant; Veterans; Work; affective psychoses; base; clinically relevant; cognitive function; cohort; disorder risk; effective therapy; endophenotype; functional disability; genetic risk factor; genetic variant; genome wide association study; innovation; neuropsychiatry; novel; prospective; psychotic symptoms; public health relevance; risk variant; social; therapy development; trait

DESCRIPTION (provided by applicant): Data from family-based, candidate gene, and genome-wide association studies converge to suggest a significant overlap in the molecular genetic risk factors for schizophrenia (SZ) and bipolar disorder (BD). This suggests that overlapping genetic variants that influence risk for these illnesses do so via effects on shared dimensional phenotypes. Among these shared traits, neurocognitive impairment, is of particular clinical relevance as it does not adequately respond to available treatments and it is among the strongest predictors of functional disability across both disorders. Moreover, there is strong evidence that neurocognitive impairment is influenced by genetic factors in both SZ and BD, making this an endophenotype which is critical toward understanding trans-disorder pathophysiology. The identification of the relevant molecular networks associated with neurocognitive functioning in psychosis is not only an important step in elucidating the causes of these disorders, but also in identifying novel treatment options for this disabling symptom domain. We will focus on neurocognition as a critical dimension that is directly associated with disease risk and attempt to identify the clinical and molecular factors that underlie cognitive impairment in psychosis. To do so, we will characterize a prospective sample of 300 patients with psychosis, including both affective and non-affective psychosis, and empirically classify subjects based on neurocognitive performance profiles. We will also collect blood samples for DNA extraction and genotype a targeted list of high priority SNPs (based on prior association with BD/SZ risk and/or neurocognitive functioning) using a customized array. These data will be applied to a multidimensional modeling analyses in an effort to identify the risk alleles and molecular pathways that contribute to neurocognitive impairment in psychosis.

描述（由申请人提供）： 来自以家族为基础的、候选基因和全基因组关联研究的数据表明，精神分裂症（SZ）和双相情感障碍（BD）的分子遗传危险因素存在显著重叠。这表明影响这些疾病风险的重叠遗传变异是通过对共享维度表型的影响来实现的。在这些共有的特征中，神经认知障碍具有特别的临床相关性，因为它对现有的治疗没有充分的反应，并且它是两种疾病中功能障碍的最强预测因子之一。此外，有强有力的证据表明，神经认知障碍是由遗传因素在SZ和BD，使这是一个内在的表型，这是了解跨疾病的病理生理学的关键。识别与精神病神经认知功能相关的相关分子网络不仅是阐明这些疾病原因的重要一步，而且也是确定这种致残症状域的新治疗方案的重要一步。我们将把重点放在神经认知作为一个关键的维度，这是直接与疾病的风险，并试图确定精神病认知障碍的基础的临床和分子因素。要做到这一点，我们将描述一个前瞻性样本的300例精神病患者，包括情感和非情感性精神病，并根据神经认知性能配置文件的基础上经验分类科目。我们还将收集血液样本用于DNA提取，并使用定制阵列对高优先级SNP的目标列表进行基因分型（基于先前与BD/SZ风险和/或神经认知功能的关联）。这些数据将应用于多维建模分析，以确定导致精神病神经认知障碍的风险等位基因和分子通路。