Flexible multivariate models for linking multi-scale connectome and genome data in Alzheimer's disease and related disorders

用于连接阿尔茨海默病和相关疾病的多尺度连接组和基因组数据的灵活多变量模型

• 批准号: 10157432
• 负责人: VINCE D CALHOUN
• 金额: $ 14.33万
• 依托单位: GEORGIA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10157432
• 关键词: Address; Age; Alzheimer' s Disease; Award; Brain; Brain imaging; COVID-19; Communities; Computer software; Custom; Data; Data Set; Disease; Elderly; Genome; Hour; Image; Individual; Italy; Learning; Lesion; Link; Magnetic Resonance Imaging; Masks; Methods; Modeling; Neurologic Symptoms; Parents; Patients; Pattern; Protocols documentation; Scanning; Structure; X-Ray Computed Tomography; age effect; base; connectome; flexibility; follow-up; insight; ischemic lesion; repository; tool; user-friendly; web site

Abstract COVID-19 is having a major impact around the world, however we are still learning about the mechanisms and manifestations of this illness. There is considerable evidence of neurological symptoms that occur in COVID-19 patients. However the impact of this, and its relationship with age, on brain structure have not been studies at all thus far. We propose to use multivariate approaches to extract covarying brain patterns from individuals to study changes associated with COVID-19 as well as potential interactions with age in older individuals. We will leverage the approaches being developed as part of the parent award, but customize them to incorporate spatial priors to address ischemic lesions. We will evaluate COVID-19 and age effects on these networks and compare them with networks extracted from normative data. We will share the methods via user friendly tools. Results are expected to provide insights into the neurological manifestations of COVID-19 including age specific effects.

抽象的 COVID-19 正在世界范围内产生重大影响，但我们仍在了解 这种疾病的机制和表现。有相当多的神经学证据 COVID-19 患者出现的症状。然而，这种影响及其与 迄今为止，年龄对大脑结构的影响尚未得到研究。我们建议使用多元 从个体中提取共变大脑模式以研究与相关变化相关的方法 COVID-19 以及老年人与年龄的潜在相互作用。我们将利用 作为家长奖励的一部分正在开发的方法，但可以定制它们以纳入 空间先验来解决缺血性病变。我们将评估 COVID-19 和年龄对这些的影响 网络并将它们与从规范数据中提取的网络进行比较。我们将分享 通过用户友好的工具的方法。预计结果将为神经学提供见解 COVID-19 的表现，包括年龄特异性影响。

项目成果

Neurotransmitter imbalance dysregulates brain dynamic fluidity in frontotemporal degeneration.

额颞叶变性中神经递质失衡会导致大脑动态流动性失调。

• 发表时间: 2020
• 影响因子: 4.2
• 作者: Benussi, Alberto;Premi, Enrico;Gazzina, Stefano;Cantoni, Valentina;Cotelli, Maria Sofia;Giunta, Marcello;Gasparotti, Roberto;Calhoun, Vince D;Borroni, Barbara
• 通讯作者: Borroni, Barbara

Alterations of frontal-temporal gray matter volume associate with clinical measures of older adults with COVID-19.

额颞叶灰质体积的变化与患有 COVID-19 的老年人的临床指标相关。

• 发表时间: 2021-05
• 作者: Duan, Kuaikuai;Premi, Enrico;Pilotto, Andrea;Cristillo, Viviana;Benussi, Alberto;Libri, Ilenia;Giunta, Marcello;Bockholt, H Jeremy;Liu, Jingyu;Campora, Riccardo;Pezzini, Alessandro;Gasparotti, Roberto;Magoni, Mauro;Padovani, Alessandro;Calho
• 通讯作者: Calho

A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic.

用于筛查 COVID-19 大流行期间精神疾病症状的快速在线调查问卷。

• 发表时间: 2022-08-04
• 影响因子: 6.8
• 作者: Chen, Fang;Yan, Weizheng;Calhoun, Vince D;Yu, Linzhen;Chen, Lili;Hao, Xiaoyi;Zheng, Leilei
• 通讯作者: Zheng, Leilei

The Influence of Cerebral Small Vessel Disease on Static and Dynamic Functional Network Connectivity in Subjects Along Alzheimer's Disease Continuum.

脑小血管疾病对阿尔茨海默病连续体受试者静态和动态功能网络连接的影响。

• 发表时间: 2021
• 影响因子: 3.4
• 作者: Li, Kaicheng;Fu, Zening;Luo, Xiao;Zeng, Qingze;Huang, Peiyu;Zhang, Minming;Vince, Calhoun D
• 通讯作者: Vince, Calhoun D

Parallel Multilink Group Joint ICA: Fusion of 3D Structural and 4D Functional Data Across Multiple Resting fMRI Networks.

并行多链路组联合 ICA：跨多个静息 fMRI 网络融合 3D 结构和 4D 功能数据。

• 发表时间: 2024-03-27
• 作者: Khalilullah, K M Ibrahim;Agcaoglu, Oktay;Sui, Jing;Duda, Marlena;Adali, Tülay;Calhoun, Vince D
• 通讯作者: Calhoun, Vince D