Association of 3.0-T Brain Magnetic Resonance Imaging Biomarkers With Cognitive Function in the Dallas Heart Study
Association of 3.0-T Brain Magnetic Resonance Imaging Biomarkers With Cognitive Function in the Dallas Heart Study
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DOI：
10.1001/jamaneurol.2014.3418
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发表时间：
2015-02-01
期刊：
影响因子：
29
通讯作者：
Peshock, Ronald M.
中科院分区：
文献类型：
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作者：
Gupta, Mohit;King, Kevin S.;Peshock, Ronald M.
由于评估脑成像的方法不一致，样本量小，以及基于危险因素的有偏见选择的种族/民族同质队列，限制了对年龄相关的脑结构变化和认知功能之间关系的理解。这些限制阻碍了脑形态学研究结果的推广。目的在多种族/多民族、以人群为基础的达拉斯心脏研究中，确定3.0-T结构脑磁共振（MR）成像测量与认知功能的关系。设计、环境和参与者：1645名达拉斯心脏研究参与者（平均[SD]年龄49.9[10.5]岁，年龄范围19-85岁）在2007年9月18日至2009年12月28日期间接受了脑MR成像和蒙特利尔认知评估的认知筛查，对3.0 T的全脑、二维、液体衰减的反演恢复和三维、磁化制备的梯度echoMR快速采集进行了研究。测量白质高强度体积、脑总体积、灰质体积、白质体积、脑脊液体积和海马体积。我们开发了线性回归和最佳预测模型，以确定MR成像生物标志物与蒙特利尔认知评估总分和领域特定问题的关联。主要结果和测量采用高分辨率解剖磁共振成像来量化脑容量。筛选蒙特利尔认知评估的得分用于参与者的认知评估。结果在调整人口统计学变量后，脑总容量（P < 0.0001，标准化估计[SE] = 0.1069）、灰质体积（P < 0.0001, SE = 0.1156）、白质体积（P = 0.008, SE = 0.087）、脑脊液体积（P = 0.012, SE = - 0.067）和海马体积（P < 0.0001）与认知能力显著相关。最佳预测模型确定灰质体积（P < 0.001, SE = 0.0021）、脑脊液体积（P = 0.01, SE = 0.0024）和海马体积（P = 0.004, SE = 0.1017）是与蒙特利尔认知评估总分显著相关的3个脑MR成像生物标志物。特定于视觉空间域的问题与最多的脑磁共振成像生物标志物（脑总量、灰质体积、白质体积、脑脊液体积和海马体积）相关，而特定于定向域的问题与最少的脑磁共振成像生物标志物相关（仅海马体积）。脑MR成像体积，包括脑总体积、灰质体积、脑脊液体积和海马体积，与认知功能独立相关，可能是年轻多种族/多民族人群认知损伤风险的重要早期生物标志物。最佳预测模型表明，多种神经成像生物标志物的组合可能比单一脑磁共振成像体积测量更有效。
IMPORTANCE Understanding the relationships between age-related changes in brain structure and cognitive function has been limited by inconsistent methods for assessing brain imaging, small sample sizes, and racially/ethnically homogeneous cohorts with biased selection based on risk factors. These limitations have prevented the generalizability of results from brain morphology studies.OBJECTIVE To determine the association of 3.0-T structural brain magnetic resonance (MR) imaging measurements with cognitive function in the multiracial/multiethnic, population-based Dallas Heart Study.DESIGN, SETTING, AND PARTICIPANTS Whole-brain, 2-dimensional, fluid-attenuated inversion recovery and 3-dimensional, magnetization-prepared, rapid acquisition with gradient echoMR imaging at 3.0 T was performed in 1645 Dallas Heart Study participants (mean [SD] age, 49.9 [10.5] years; age range, 19-85 years) who received both brain MR imaging and cognitive screening with the Montreal Cognitive Assessment between September 18, 2007, and December 28, 2009. Measurements were obtained for white matter hyperintensity volume, total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume. Linear regression and a best predictive model were developed to determine the association of MR imaging biomarkers with the Montreal Cognitive Assessment total score and domain-specific questions.MAIN OUTCOMES AND MEASURES High-resolution anatomical MR imaging was used to quantify brain volumes. Scores on the screening Montreal Cognitive Assessment were used for cognitive assessment in participants.RESULTS After adjustment for demographic variables, total brain volume (P < .0001, standardized estimate [SE] = .1069), gray matter volume (P < .0001, SE = .1156), white matter volume (P = .008, SE = .0687), cerebrospinal fluid volume (P = .012, SE = -.0667), and hippocampal volume (P < .0001) were significantly associated with cognitive performance. A best predictive model identified gray matter volume (P < .001, SE = .0021), cerebrospinal fluid volume (P = .01, SE = .0024), and hippocampal volume (P = .004, SE = .1017) as 3 brain MR imaging biomarkers significantly associated with the Montreal Cognitive Assessment total score. Questions specific to the visuospatial domain were associated with the most brain MR imaging biomarkers (total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume), while questions specific to the orientation domain were associated with the least brain MR imaging biomarkers (only hippocampal volume).CONCLUSIONS AND RELEVANCE Brain MR imaging volumes, including total brain volume, gray matter volume, cerebrospinal fluid volume, and hippocampal volume, were independently associated with cognitive function and may be important early biomarkers of risk for cognitive insult in a young multiracial/multiethnic population. A best predictive model indicated that a combination of multiple neuroimaging biomarkers may be more effective than a single brain MR imaging volume measurement.