43,160人的多病症和疾病群与大脑健康的神经影像学和认知标记之间的关系。

Shehab Uddin Al Abid, Catherine M Calvin, Danial Qureshi, Michele Veldsman, El¿bieta Kuÿma, Thomas J. Littlejohns
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引用次数: 0

摘要

背景:最近的研究发现,患有两种或两种以上慢性疾病(称为多病共存)的人患痴呆症的风险会增加。在本研究中,我们调查了多病共存是否与一系列痴呆症相关的神经影像学和认知标记物有关,这些标记物通常在临床诊断痴呆症之前就已表现出来。研究方法我们纳入了 43160 名年龄在 45-83 岁之间、无神经系统疾病(包括痴呆症)的参与者,他们在 2014 年以后参加了英国生物库成像评估。多病症的定义是从 39 种病症的标准化标准中挑选出的 ³2 种长期病症。潜类分析用于识别疾病群。神经影像学结果通过磁共振成像(MRI)进行测量,认知能力通过七项测量不同认知领域的测试进行评估。线性回归模型经社会人口学和神经成像混杂因素调整后,用于检验多病和疾病群与神经成像和认知结果之间的关联。结果显示14339名参与者(33.2%)患有多病症。在完全调整模型中,存在多病与几种较差的大脑健康状况相关。这包括灰质体积较低(b:-0.03 标准差 (SD);95% 置信区间 (CI):-0.04,-0.02)、全脑体积较低(b:-0.01 [-0.02,-0.01])、左侧海马体积较低(b:-0.03 [-0.05,-0.01])、白质过多体积较低 (b:-0.03 [-0.05,-0.01])、白质过多体积较高 (b:-0.03 [-0.05,-0.01])01])、白质高密度体积增加(v:0.09 [0.07, 0.10])、执行功能(b:0.04 [0.02, 0.06])、言语陈述记忆(b:-0.03 [-0.05, -0.01])和处理速度(b:-0.07 [-0.10, -0.05])较差。多重疾病数量的增加与上述结果之间存在强烈的剂量反应关系。不同疾病群组之间的关联强度各不相同,以心血管代谢疾病为主的疾病群组与脑健康结果的关联度最高。由 "呼吸系统"、"精神健康 "和 "其他 "疾病引起的疾病群与神经影像和认知结果的相关性不一致。结论多病(主要是心血管代谢性多病)与较差的脑健康相关。这些发现让我们了解了之前观察到的多病症与痴呆症风险之间关联的潜在途径:162
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association of multimorbidity and disease clusters with neuroimaging and cognitive markers of brain health in 43,160 individuals.
Background: Recent research has found that living with two or more chronic conditions, termed multimorbidity, is associated with an increased risk of developing dementia. In the current study, we investigated whether multimorbidity is associated with a range of dementia-related neuroimaging and cognitive markers of brain health that typically manifest prior to a clinical diagnosis of dementia. Methods: We included 43,160 participants aged 45-83 years free from neurological conditions, including dementia, who attended the UK Biobank imaging assessment from 2014-onwards. Multimorbidity was defined as the presence of ³2 long-term conditions from a standardised criteria of 39 conditions. Latent class analyses were used to identify disease clusters. Neuroimaging outcomes were measured using magnetic resonance imaging (MRI), and cognition was assessed by seven tests measuring different cognitive domains. Linear regression models, adjusted for socio-demographic and neuroimaging confounders, were used to test the association between multimorbidity and disease clusters with neuroimaging and cognitive outcomes. Results: Multimorbidity was present among 14,339 (33.2%) participants. In fully-adjusted models, presence of multimorbidity was associated with several measures of poorer brain health. This included lower volumes of grey matter (b: -0.03 standard deviation (SD); 95% confidence interval (CI): -0.04, -0.02), total brain (b: -0.01 [-0.02, -0.01]), left hippocampus (b: -0.03 [-0.05, -0.01]), increased white matter hyperintensity volume (v: 0.09 [0.07, 0.10]), poorer executive function (b: 0.04 [0.02, 0.06]), verbal declarative memory (b: -0.03 [-0.05, -0.01]), and processing speed (b: -0.07 [-0.10, -0.05]). A strong dose-response relationship was observed with the increasing number of multimorbid conditions and the aforementioned outcomes. Strength of associations varied across disease clusters, with a cluster predominantly driven by cardio-metabolic conditions showing the strongest associations with brain health outcomes. Clusters driven by ‘respiratory’, ‘mental health’ and ‘miscellaneous’ conditions were inconsistently associated with neuroimaging and cognitive outcomes. Conclusion: Multimorbidity, primarily cardio-metabolic multimorbidity, was associated with poorer brain health. These findings provide insights into the potential pathways underlying previously observed associations between multimorbidity and dementia risk. Bangladesh J Medicine 2024; Vol. 35, No. 2, Supplementation: 162
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