Longitudinal neuroimaging and neurocognitive assessment of risk and protective factors across the schizophrenia spectrum

精神分裂症谱系风险和保护因素的纵向神经影像和神经认知评估

• 批准号: 10319171
• 负责人: ERIN A. HAZLETT
• 金额: $ 99.89万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-06 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10319171
• 关键词: Age; Antipsychotic Agents; Attenuated; Brain; Brain region; Brodmann' s area; Clinical; Clinical assessments; Cognition; Cognitive deficits; Coupled; Data; Deterioration; Diagnosis; Diagnostic; Diffusion Magnetic Resonance Imaging; Disease; Etiology; Event; Functional Magnetic Resonance Imaging; Genetic; Goals; Hospitalization; Impairment; Individual; Investigation; Link; Longitudinal Studies; Machine Learning; Magnetic Resonance Imaging; Measures; Modeling; Neurobiology; Neurocognition; Neurocognitive; Neuropsychology; Onset of illness; Outcome; Pathogenesis; Patients; Pattern; Performance; Personality Disorders; Pharmaceutical Preparations; Phenotype; Prefrontal Cortex; Psychoses; Research Domain Criteria; Rest; Risk; Risk Assessment; Risk Factors; Scanning; Schizophrenia; Schizotypal Personality Disorder; Severities; Short-Term Memory; Structure; Symptoms; Temporal Lobe; Testing; Time; Treatment Factor; Ursidae Family; base; causal model; early onset; follow-up; frontal lobe; functional outcomes; improved; longitudinal course; longitudinal design; morphogens; multimodal neuroimaging; multimodality; neural circuit; neuroimaging; novel strategies; predictive modeling; protective factors; resilience; schizophrenia-spectrum disorder; social deficits; white matter

PROJECT SUMMARY Schizotypal personality disorder (SPD) is similar to schizophrenia (SZ), but with fewer and attenuated abnormalities, thus representing an important yet understudied intermediate SZ-spectrum phenotype. Examination of abnormalities in SPD will provide information regarding etiology, genetics, treatment and risk factors associated with psychosis. Although individuals with SPD demonstrate marked temporal lobe abnormalities that resemble SZ, we hypothesize that relative “sparing” or “functional enhancement” in the frontal lobes (e.g., dorsolateral prefrontal cortex), may protect these individuals from frank psychosis and the severe social and cognitive deficits typically observed in SZ. Studying SPD is powerful as antipsychotic medication and hospitalization confounds observed in SZ are not present. Moreover, there is no study examining neurobiological changes in the SZ-spectrum that incorporates individuals with SPD using a longitudinal design as proposed here. This novel approach will help disentangle potential risk and protective factors for psychosis in the SZ spectrum. This is the first longitudinal study to utilize multimodal MR imaging and Research Domain Criteria (RDoC) approaches in SZ-spectrum disorders to identify aberrant neural circuitry along a continuum from healthy controls (HCs) to SPD to SZ and examine changes in these measures in relationship to impairments in symptom severity, neurocognition and functional outcome. We propose studying three groups (80 in each) of demographically matched and rigorously diagnosed individuals (age 18- 40): HCs (no Axis I or personality disorder), unmedicated individuals with SPD (and no Axis I disorder), and early-onset (first 2 years of illness) SZ patients at baseline, 9-, and 18-month follow-up. Measures assessing frontal and temporal lobe integrity include multimodal MR imaging (structural MRI, DTI, resting-state fMRI, and task-based fMRI with a nonverbal event related working-memory task; baseline and 18-months) and neuropsychological assessment (all three timepoints). We will utilize dynamic causal modeling to test competing neurobiological models involving abnormal frontotemporal connectivity in the SZ-spectrum and machine learning approaches to integrate multimodal neuroimaging, neurocognitive, and clinical assessment data. We focus on three specific aims: (1) Investigate the longitudinal course of frontal-temporal lobe/circuitry abnormalities in the SZ-spectrum using multimodal MR imaging; (2) Investigate the longitudinal course of neurocognition, clinical, and functional outcome in the SZ spectrum; (3) Determine which factor or combination of factors differentiate groups in the SZ-spectrum to identify those that are associated with risk for and protection from SZ using machine learning.

项目摘要 分裂型人格障碍（SPD）与精神分裂症（SZ）相似，但数量较少， 异常，因此代表了一个重要的但研究不足的中间SZ谱表型。 SPD的异常检查将提供有关病因、遗传学、治疗和风险的信息 与精神病有关的因素虽然SPD患者的颞叶 类似SZ的异常，我们假设，相对的“保留”或“功能增强”， 额叶（例如，背外侧前额叶皮层），可能会保护这些人从坦率的精神病和 严重的社交和认知缺陷通常在SZ中观察到。研究SPD是强大的抗精神病药 在SZ中未观察到药物和住院混淆。此外，没有任何研究 检查神经生物学的变化，在SZ频谱，包括个人与SPD使用 纵向设计如本文所述。这种新颖的方法将有助于解开潜在的风险和保护 SZ谱系中的精神病因素。这是第一个纵向研究，利用多模态磁共振成像 和研究领域标准（RDOC）方法用于识别ZZ谱系疾病的异常神经 电路沿着从健康对照（HC）到SPD到SZ的连续体，并检查这些措施的变化 与症状严重程度、神经认知和功能结果损害的关系。我们提出 研究了三组（每组80人）人口统计学匹配和严格诊断的个体（18岁- 40）：HC（无轴I或人格障碍），未用药的SPD个体（无轴I障碍），以及 基线、9个月和18个月随访时的早发（患病前2年）SZ患者。措施评估 额叶和颞叶的完整性包括多模态MR成像（结构MRI、DTI、静息状态fMRI和 基于任务的功能磁共振成像与非语言事件相关的工作记忆任务;基线和18个月）， 神经心理学评估（所有三个时间点）。我们将利用动态因果模型来测试 涉及SZ频谱中异常额颞连接的竞争神经生物学模型， 整合多模态神经成像、神经认知和临床评估的机器学习方法 数据本研究的主要目的有三：（1）研究额颞叶/脑回路的纵向走行 使用多模态MR成像检查SZ频谱异常;（2）研究 SZ频谱中的神经认知、临床和功能结局;（3）确定哪些因素或组合 的因素区分SZ谱中的组，以确定那些与风险相关的因素， 使用机器学习保护SZ。