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.

摘要 COVID-19正在世界各地产生重大影响，但我们仍在了解 这种疾病的机制和表现。有相当多的证据表明 COVID-19患者出现的症状。然而，这一影响及其与 年龄对大脑结构的影响迄今为止还没有研究过。我们建议使用多变量 从个体中提取共变脑模式的方法，以研究与 COVID-19以及与老年人年龄的潜在相互作用。我们将利用 正在制定的方法作为母公司奖励的一部分，但对其进行定制，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，并将其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。研究结果有望为神经系统疾病的研究提供新的见解。 COVID-19的表现，包括年龄特异性影响。

项目成果

Multimodal fusion of multiple rest fMRI networks and MRI gray matter via parallel multilink joint ICA reveals highly significant function/structure coupling in Alzheimer's disease.

• DOI: 10.1002/hbm.26456
• 发表时间: 2023-10-15
• 期刊: HUMAN BRAIN MAPPING
• 影响因子: 4.8
• 作者: Khalilullah, K. M. Ibrahim;Agcaoglu, Oktay;Sui, Jing;Adali, Tulay;Duda, Marlena;Calhoun, Vince D.
• 通讯作者: Calhoun, Vince D.

Neuropsychiatric symptoms associated multimodal brain networks in Alzheimer's disease.

• DOI: 10.1002/hbm.26051
• 发表时间: 2023-01
• 期刊: Human brain mapping
• 影响因子: 4.8

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

• DOI: 10.1016/j.ynstr.2021.100326
• 发表时间: 2021-05
• 期刊: Neurobiology of stress
• 影响因子: 5
• 作者: Duan K;Premi E;Pilotto A;Cristillo V;Benussi A;Libri I;Giunta M;Bockholt HJ;Liu J;Campora R;Pezzini A;Gasparotti R;Magoni M;Padovani A;Calhoun VD
• 通讯作者: Calhoun VD

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

• DOI: 10.1038/s41398-022-02086-7
• 发表时间: 2022-08-04
• 期刊: TRANSLATIONAL PSYCHIATRY
• 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