Cardiometabolic risk factors associated with brain age and accelerate brain ageing.

Cardiometabolic risk factors associated with brain age and accelerate brain ageing.
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DOI:
10.1002/hbm.25680
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发表时间:
2022-02-01
影响因子:
4.8
通讯作者:
Westlye LT
Westlye LT
中科院分区:
医学2区
文献类型:
--
作者:
Beck D;de Lange AG;Pedersen ML;Alnaes D;Maximov II;Voldsbekk I;Richard G;Sanders AM;Ulrichsen KM;Dørum ES;Kolskår KK;Høgestøl EA;Steen NE;Djurovic S;Andreassen OA;Nordvik JE;Kaufmann T;Westlye LT

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衰老大脑的结构和完整性与身体健康有着可互换的联系,而心脏代谢风险因素(CMR)与痴呆症和其他脑部疾病有关。在这项混合横断面和纵向研究中(平均间隔= 19.7个月),包括790名健康个体(平均年龄= 46.7岁,53%为女性),我们使用基于MRI的形态测量和弥散张量成像(DTI)研究了CMR和健康指标,包括人体测量指标,生活方式因素和与脑结构相关的血液生物标志物。我们使用机器学习进行了组织特异性脑年龄预测,并进行了贝叶斯多水平建模,以评估每种CMR随时间的变化,它们各自与脑年龄差距(BAG)的相关性,以及它们与时间和年龄对组织特异性BAG的相互作用。结果显示,基于DTI的BAG与血液磷酸盐水平和平均细胞体积(MCV)之间存在可靠的相关性,基于T1的BAG与收缩压,吸烟,脉搏和C反应蛋白(CRP)之间存在可靠的相关性,表明心脏代谢风险较高(吸烟,血压和脉搏较高,低度炎症)的人的大脑出现老年化。纵向证据支持BAG与腰臀比(WHR)之间的相互作用,以及基于DTI的BAG与收缩压和吸烟之间的相互作用,表明具有较高心脏代谢风险(吸烟,高血压和WHR)的人加速衰老。结果表明,心脏代谢危险因素与大脑老化有关。虽然需要随机对照试验来建立因果关系,但我们的研究结果表明,针对可改变的心脏代谢风险因素的公共卫生举措和治疗策略也可能改善风险轨迹并延缓大脑衰老。衰老大脑的结构和完整性与身体健康和心脏代谢风险因素(CMR)相互关联。我们使用基于MRI的形态测量和扩散张量成像(DTI)研究了CMR和健康指标,包括人体测量指标、生活方式因素和与大脑结构相关的血液生物标志物。使用机器学习进行的组织特异性大脑年龄预测显示,在心脏代谢风险较高的人群中,大脑显得更老,衰老加速。
The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross‐sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI‐based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue‐specific BAGs. The results showed credible associations between DTI‐based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1‐based BAG and systolic blood pressure, smoking, pulse, and C‐reactive protein (CRP), indicating older‐appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low‐grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist‐to‐hip ratio (WHR), and between DTI‐based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing. The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs). We investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI‐based morphometry and diffusion tensor imaging (DTI). Tissue‐specific brain age prediction using machine learning revealed older‐appearing brains and accelerated ageing in people with higher cardiometabolic risk.
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