An integrative computational interrogation of circuit dysfunction inschizophrenia via neural timescales

通过神经时间尺度对精神分裂症中的回路功能障碍进行综合计算询问

• 批准号: 10704693
• 负责人: Guillermo Horga
• 金额: $ 72.2万
• 依托单位: NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10704693
• 关键词: Address; Anxiety Disorders; Architecture; Automobile Driving; Biological; Biological Markers; Biophysics; Brain region; Cells; Clinical; Cognition; Cognitive; Cognitive deficits; Complement; Complex; Computer Models; Data; Data Reporting; Data Set; Development; Developmental Process; Diagnosis; Disease; Disparate; Distal; Equilibrium; Etiology; Exhibits; Foundations; Functional Magnetic Resonance Imaging; Functional disorder; General Population; Genetic; Genotype; Human; Hybrids; Impairment; Individual; Interneurons; Link; Longevity; Measures; Mediating; Mediator; Memory impairment; Mental disorders; Methods; Mood Disorders; Neurocognitive; Neurocognitive Deficit; Neurons; Pathway interactions; Patient Self-Report; Patients; Perception; Performance; Phenotype; Population; Process; Psychoses; Public Health; Recurrence; Reporting; Rest; Risk; Role; Schizophrenia; Selection for Treatments; Severities; Shapes; Short-Term Memory; Specificity; Testing; Validation; Work; age related; behavioral phenotyping; biobank; biophysical model; brain based; candidate marker; cell cortex; cell type; cognitive function; comparison control; connectome; connectome data; course development; early onset; genetic risk factor; genetic variant; genome wide association study; hippocampal pyramidal neuron; human disease; indexing; interest; large datasets; large scale data; multimodal data; neural; novel; operation; phenomenological models; psychotic symptoms; response; risk variant; schizophrenia risk; secondary analysis; social stigma; theories; trait

SUMMARY/ABSTRACT Schizophrenia is a devastating and burdensome illness the mechanisms of which remain elusive. Contributing to their elusiveness are a highly complex set of genetic factors, proposed etiological and pathophysiological pathways, and phenotypic manifestations. To address this complexity, we propose a hybrid method combining data-driven approaches to large-scale multimodal datasets and theory-driven computational approaches in order to provide a theoretically constrained framework bridging genetics, development, circuit function, cognition, and phenomenology of schizophrenia. To that end, and in response to ‘Notice of Special Interest regarding the Use of Human Connectome Data (HCP) for Secondary Analysis’, we will use data from up to 64,000 individuals, including healthy individuals and patients with schizophrenia and other disorders, from various HCP-related projects as well as the UK Biobank. We specifically propose measuring intrinsic neural timescales (INT) from resting-state fMRI data as a theory-driven index of excitation/inhibition (E/I) imbalance in cortical microcircuits. First, extending our prior work we aim to confirm and further characterize INT alterations in schizophrenia (widespread trait-like INT reductions and local hierarchy-dependent INT modulations in relation to psychotic symptoms) and to test their specificity relative to other disorders. Second, we will evaluate the developmental trajectories of INT and characterize the genetic profile of this fMRI measure and its overlap with the genetic profile for schizophrenia risk. Third, given the role of E/I ratio in cortical microcircuits in supporting working-memory computations, we will examine the relationship between INT and working-memory activation and performance. We will further seek to establish INT as a circuit-level mediator of polygenic risk for schizophrenia on cognitive deficits. Throughout, we will use well-powered, rigorous, state-of-the-art fMRI and statistical data-driven methods suitable for large-scale studies and HCP-style fMRI sequences, including cross- validation and tests of generalizability. Together with a strong theoretical foundation and using biophysical modeling to complement fMRI analyses, this hybrid—theory- and data-driven—approach will facilitate an integrated understanding of the circuit-level mechanisms bridging distal genetic-risk factors and proximal manifestations of schizophrenia. In particular, the combination of cutting-edge cell-type enrichment analyses of GWAS (which in schizophrenia have suggested converging enrichment in excitatory and inhibitory cortical cells) and biophysical modeling at the level of cortical microcircuits of interacting excitatory and inhibitory cellular populations will provide an interpretation of disparate data in terms of convergent cell- and circuit-level pathways. In doing so, this project will validate a theoretically informative, interpretable, translatable, and scalable resting-state fMRI measure—INT—that may be relevant across several disorders and, which additionally owing to its high reliability and ease of acquisition, has high potential as a candidate biomarker.

摘要/摘要 精神分裂症是一种毁灭性的、造成负担的疾病，其发病机制仍然难以捉摸。 其难以捉摸的是一组高度复杂的遗传因素，提出了病因学和病理生理学 为了解决这种复杂性，我们提出了一种结合的混合方法。 大规模多模态数据集的数据驱动方法和理论驱动的计算方法 为了提供一个连接遗传学、发育、电路功能的理论约束框架， 为此，并响应“特别兴趣通知”。 关于使用人类连接组数据 (HCP) 进行二次分析”，我们将使用来自最多 64,000 名个体，包括健康个体以及患有精神分裂症和其他疾病的患者，来自 各种 HCP 相关项目以及英国生物库我们特别建议测量内在神经。 静息态功能磁共振成像数据的时间尺度（INT）作为激发/抑制（E/I）不平衡的理论驱动指数 首先，扩展我们之前的工作，我们的目标是确认并进一步表征 INT 的改变。 在精神分裂症中（广泛的性状 INT 降低和局部层次依赖的 INT 调节） 与精神病症状的关系）并测试其相对于其他疾病的特异性 其次，我们将评估。 INT 的发展轨迹并描述该功能磁共振成像测量的遗传特征及其重叠 第三，考虑到 E/I 比在大脑皮层微电路中的作用。 支持工作内存计算，我们将检查 INT 和工作内存之间的关系 我们将进一步寻求将 INT 建立为多基因风险的回路水平中介。 在整个过程中，我们将使用功能强大、严格、最先进的功能磁共振成像和 适用于大规模研究和 HCP 型 fMRI 序列的统计数据驱动方法，包括交叉 具有强大的理论基础并利用生物物理学进行验证和测试。 通过建模来补充功能磁共振成像分析，这种理论和数据驱动的混合方法将促进 对桥接远端遗传风险因素和近端遗传风险因素的回路级机制的综合理解 特别是结合了尖端细胞类型富集分析。 GWAS（在精神分裂症中表明兴奋性和抑制性皮质的集中富集） 细胞）和相互作用的兴奋性和抑制性皮质微电路水平的生物物理建模 细胞群体将在融合细胞和电路水平方面提供对不同数据的解释 在此过程中，该项目将验证理论上的信息丰富、可解释、可翻译和 可扩展的静息态功能磁共振成像测量——INT——可能与多种疾病相关，并且， 此外，由于其高可靠性和易于获取，作为候选生物标志物具有很高的潜力。