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）：仅由临床现象学定义，主要的精神病（SZ，SAD，BDP）在神经生物学，生物标志物，合并，症状和遗传特征上广泛重叠。当在疾病的定义和鉴定中考虑生物学变量时，我们的领域可能受益于其他医学领域的疾病的转化重新概念化。精神病学中的这种方法将取决于：（i）使用良好的疾病领域，（ii）捕获临床异质性和支持统计方法的大型样本，以及（iii）获得可量化的实验室测量的能力t t告知疾病特征的重新概念化。 5点B-SNIP焦点是精神病，这是为此目的的理想临床表型。 B- SNIP1招募了2500多名志愿者，并在多个分析（认知，心理生理学，脑成像，社交和临床上）进行了密集的表型。总体数据描述了DSM精神病诊断（BDP，SAD，SZ）的表型改变的连续性，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性来定义基于生物学的亚组，我们使用生物标志物和多阶段的多变量分析程序重新组成了概率。我们根据核心表型特征确定了3种精神病“生物型”。生物型显示出在类别初始构造中未使用的外部验证器之间的独特差异。 B-SNIP2将使用增强的概率数，生物标志物面板以及多元统计方法的复杂性复制和扩展B-SNIP1。我们将在两个特定目标的背景下实现我们的目标。 SA（1）构建了“精神病生物标志物数据库”（PBD）：招募3000种新的精神病概率和600名健康志愿者，并收集包括临床，心理社会，电生理学，眼运动，成像，成像和血液生物标志物的数据。将按照指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Broad Institute合作获得。 SA（2）根据PBD中的数据，基于临床变量，（III）B-SNIP1 Biotypes，（III）Bioty ot ot Bibiot，（III）Bioty，（III）Biotipes，（ii）Biip1-iv-snipypes，（ii），对比和测试分类进行分类的精神病：评估不同分类学结构定义精神病亚组的能力。 （v）基于临床变量和生物标志物的B-SNIP2生物型。从传统的DSM诊断标准开始作为分类学和测试（i） - （v）我们将使用线性，二次和非参数判别功能分析应用于外部生物标志物验证器，以检查传统诊断系统与生物学衍生的分类（成像，心理社会和遗传外部验证者）之间的关联。我们将能够根据生物学特征来确定最强的分类方法。我们寻求对精神病疾病的合理分类，这些分类将成功识别新型疾病 目标和治疗方法。