5/5 BIPOLAR-SCHIZOPHRENIA NETWORK FOR INTERMEDIATE PHENOTYPES (B-SNIP) - Resubmission - 1

5/5 中间表型的双极精神分裂症网络 (B-SNIP) - 重新提交 - 1

• 批准号: 9338010
• 负责人: BRETT A CLEMENTZ
• 金额: $ 16.53万
• 依托单位: UNIVERSITY OF GEORGIA
• 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/9338010
• 关键词: Address; Area; Biologic Characteristic; Biological; Biological Markers; Bipolar Disorder; Blood; Brain; Brain imaging; Categories; Characteristics; Classification; Classification Scheme; Clinical; Cognitive; Collaborations; Comorbidity; 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; relating to nervous system; social; volunteer

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 welldefined disease domains, (ii) large samples that capture clinical heterogeneity and support statistical approaches, and (iii) ability to acquire quantifiable laboratory measures to inform re-conceptualization of disease characteristics. The 5-site B-SNIP focus is psychosis, an ideal clinical phenotype for this purpose. BSNIP1 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 BSNIP1 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 collaboration with the Broad Institute. SA(2) Contrast and test taxometric approaches to categorizing psychosis: Evaluate the ability of different toxonomic 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 biologicallyderived 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.

主要精神病（SZ，SAD，BDP），当仅由临床现象学定义时， 神经生物学、生物标志物、共病、症状和遗传特征。我们的领域可能受益于 当生物学变量被 在疾病定义和识别中考虑。精神病学的这种方法将取决于：（i）使用定义明确的 疾病领域，（ii）捕获临床异质性并支持统计学的大样本 （三）能够获得可量化的实验室措施，为重新构想 疾病特征5位点B-SNIP病灶是精神病，这是用于此目的的理想临床表型。BSNIP1 招募了超过2500名志愿者，并在多个水平的分析中进行了密集的表型分析 （认知、心理生理、脑成像、社会和临床）。总体数据描述了一个连续的 DSM精神病诊断（BDP、SAD、SZ）中的表型改变，几乎没有诊断性证据 的特异性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重新分组。我们发现3 基于核心表型特征的“生物型”。生物型在外部环境中表现出独特的差异 在类别的初始构造中未使用的验证器。B-SNIP 2将复制和扩展BSNIP 1 使用增强的先证者数量、生物标志物组和多变量统计的复杂性， 接近。我们将在两个具体目标的范围内实现我们的目标。SA（1）构造一个 “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 并收集包括临床、心理社会、电生理、眼运动、成像和血液在内的数据 生物标志物。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特征）将按规定收集。遗传特点 参与者将与布罗德研究所合作获得。SA（2）对比和测试分类 精神病分类的方法：评估不同的毒理学结构的能力， 精神病亚组，基于PBD中的数据：（i）DSM，（ii）基于临床变量的B-SNIP 2生物型，（iii） B-SNIP 1生物型，（iv）基于生物标志物的B-SNIP 2生成的生物型，和（v）基于生物标志物的B-SNIP 2生物型。 包括临床变量和生物标志物。从传统的DSM诊断标准作为分类法开始， 测试（i）-（v）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衍生的 分类（成像，心理和遗传外部验证器）。我们将能够确定 基于生物学特征的最强分类方法。我们寻求一个合理的分类， 精神障碍，将成功地确定新的疾病目标和治疗方法。