2/5 Bipolar-Schizophrenia Network for Intermediate Phenotypes 2 (B-SNIP2)

2/5 中间表型的双相精神分裂症网络 2 (B-SNIP2)

• 批准号: 9293383
• 负责人: Elliot S Gershon
• 金额: $ 79.36万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9293383
• 关键词: Address; Area; Biologic Characteristic; Biological; Biological Markers; Bipolar Disorder; Blood; Brain; Brain imaging; Categories; Characteristics; Classification; Classification Scheme; Clinical; Cognitive; Complex; DSM-IV; Data; Databases; Depressed mood; Diagnosis; Diagnostic; Diagnostic Specificity; Dimensions; Disease; Electrophysiology (science); Etiology; Genetic; Goals; Heritability; Heterogeneity; Image; Institutes; Laboratories; Measures; Medicine; Molecular Genetics; Multivariate Analysis; Names; Neurobiology; Neurologic Symptoms; Outcome; Participant; Phenotype; Physiological; Positioning Attribute; Procedures; Psychiatric Diagnosis; Psychiatry; Psychophysiology; Psychotic Disorders; Recruitment Activity; Sampling; Schizoaffective Disorders; Schizophrenia; Site; Specific qualifier value; Structure; Subgroup; Symptoms; System; Taxonomy; Testing; Work; base; biomarker panel; case control; clinical phenotype; genetic analysis; healthy volunteer; neurobiological mechanism; novel; oculomotor; personalized medicine; phenomenological models; phenotypic biomarker; proband; psychosocial; public health relevance; relating to nervous system; social; volunteer

DESCRIPTION (provided by applicant): The major psychoses (SZ, SAD, BDP), when defined by clinical phenomenology alone, overlap extensively on neurobiological, biomarker, co-morbid, symptomatic, and genetic characteristics. Our field may benefit from transformational re-conceptualizations of disease seen in other areas of medicine when biological variables are considered in disease definitions and identification. This approach in psychiatry will depend on: (i) use of well- defined disease domains, (ii) large samples that capture clinical heterogeneity and support statistical approaches, and (iii) ability to acquire quantifiable laboratory measures t inform re-conceptualization of disease characteristics. The 5-site B-SNIP focus is psychosis, an ideal clinical phenotype for this purpose. B- SNIP1 recruited over 2500 volunteers and performed dense phenotyping across multiple levels of analysis (cognitive, psychophysiological, brain imaging, social and clinical). The overall data described a continuum of phenotypic alterations across the DSM psychosis diagnoses (BDP, SAD, SZ) with little evidence of diagnostic specificity. In an attempt to use these dense phenotypic characteristics to define biologically based subgroups, we re-grouped probands using biomarkers and a multistage multivariate analysis procedure. We identified 3 psychosis "Biotypes" based on core phenotypic features. Biotypes showed unique differences across external validators that were not used in the initial construction of the categories. B-SNIP2 will replicate and extend B- SNIP1 using enhanced proband number, biomarker panel, and sophistication of multivariate statistical approaches. We will accomplish our goals within the context of two specific aims. SA(1) Construct a 'Psychosis Biomarker Database' (PBD): Recruit 3000 new psychosis probands and 600 healthy volunteers and collect data including clinical, psychosocial, electrophysiological, ocular motor, imaging and blood biomarkers. Core biomarkers (used for Biotype definition) and external validators (used for verifying neurobiological distinctiveness of Biotypes) will be collected as specified. Genetic characteristics of the participants will be obtained in collaboratin with the Broad Institute. SA(2) Contrast and test taxometric approaches to categorizing psychosis: Evaluate the ability of different taxonomic structures to define psychosis subgroups, based on data in the PBD: (i) DSM, (ii) B-SNIP2 biotypes based on clinical variables, (iii) B-SNIP1 Biotypes, (iv) B-SNIP2-generated biotypes based on biomarkers, and (v) B-SNIP2 biotypes based on both clinical variables and biomarkers. Beginning with traditional DSM diagnostic criteria as the taxonomy and testing (i)-(v) we will use linear, quadratic and nonparametric discriminant function analysis applied to external biomarker validators to examine the association between the traditional diagnostic system and the biologically- derived classification (imaging, psychosocial and genetic external validators). We will be able to determine the strongest taxonomic approach based on biological characteristics. We seek a rational classification of psychotic disorders that will be successful in identifying novel disease targets and treatments approaches.

描述（由申请人提供）：当仅通过临床现象学定义时，主要精神病（SZ、SAD、BDP）在神经生物学、生物标志物、共病、症状和遗传特征上广泛重叠。当在疾病定义和识别中考虑生物变量时，我们的领域可能会受益于其他医学领域对疾病的变革性重新概念化。精神病学中的这种方法将取决于：（i）使用明确的疾病领域，（ii）捕获临床异质性并支持统计方法的大样本，以及（iii）获得可量化的实验室测量数据以告知疾病重新概念化的能力特征。 5 位点 B-SNIP 重点是精神病，这是用于此目的的理想临床表型。 B-SNIP1 招募了超过 2500 名志愿者，并在多个分析层面（认知、心理生理、脑成像、社会和临床）进行密集表型分析。总体数据描述了 DSM 精神病诊断（BDP、SAD、SZ）的一系列表型变化，几乎没有诊断特异性的证据。为了尝试使用这些密集的表型特征来定义基于生物学的亚组，我们使用生物标志物和多阶段多变量分析程序对先证者进行了重新分组。我们根据核心表型特征确定了 3 种精神病“生物型”。生物型在类别的初始构建中未使用的外部验证器之间表现出独特的差异。 B-SNIP2 将使用增强的先证者数量、生物标志物组和复杂的多元统计方法来复制和扩展 B-SNIP1。我们将在两个具体目标的背景下实现我们的目标。 SA（1）构建“精神病生物标志物数据库”（PBD）：招募3000名新的精神病先证者和600名健康志愿者，收集包括临床、心理社会、电生理、眼运动、影像和血液生物标志物在内的数据。将按照规定收集核心生物标志物（用于生物型定义）和外部验证器（用于验证生物型的神经生物学独特性）。参与者的遗传特征将与布罗德研究所合作获得。 SA(2) 对比和测试对精神病进行分类的分类方法：根据 PBD 中的数据评估不同分类结构定义精神病亚组的能力：(i) DSM，(ii) 基于临床变量的 B-SNIP2 生物型，（ iii) B-SNIP1 生物型，(iv) B-SNIP2 基于生物标志物生成的生物型，以及 (v) B-SNIP2 基于临床变量和生物标志物。从传统的 DSM 诊断标准作为分类和测试 (i)-(v) 开始，我们将使用线性、二次和非参数判别函数分析应用于外部生物标志物验证器，以检查传统诊断系统和生物学分类之间的关联（影像、社会心理和遗传外部验证器）。我们将能够根据生物学特征确定最强的分类方法。我们寻求精神障碍的合理分类，以成功识别新疾病 目标和治疗方法。