Abid Shehab Uddin Al, Calvin Catherine M, Qureshi Danial, Veldsman Michele, Kuźma Elżbieta, Littlejohns Thomas J
Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK; Health Data Research UK, University of Oxford (HDRUK-Oxford), Oxford, UK.
UK Biobank, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.
J Prev Alzheimers Dis. 2025 Aug;12(7):100208. doi: 10.1016/j.tjpad.2025.100208. Epub 2025 May 26.
The relationship between multimorbidity, particularly disease clusters, with neuroimaging and cognitive outcomes that typically manifest prior to clinical diagnosis of dementia, remains understudied. This study investigated whether multimorbidity is associated with dementia-related neuroimaging and cognitive outcomes in the UK Biobank cohort.
This cross-sectional study used data from UK Biobank participants who attended imaging assessments between 2014-2023, and were free from neurological conditions, including dementia. Multimorbidity was defined as the coexistence of two or more long-term conditions, selected from a standardised criteria of 39 conditions. Latent class analyses were used to identify disease clusters. Neuroimaging outcomes were measured using magnetic resonance imaging, and cognition was assessed by seven tests measuring different cognitive domains. Multivariable linear regression was used to assess the association between multimorbidity and disease clusters with neuroimaging and cognitive outcomes.
A total of 43,160 participants were included (mean [standard deviation] age, 64.2 [7.7] years, 53.1 % female). Multimorbidity was present among 14,339 (33.2 %) participants, and was associated with reduced grey matter volume, total brain volume, left hippocampal volume, increased cerebrovascular pathology as well as reduced domain-specific cognitive function. A strong dose-response relationship was observed with the increasing number of multimorbid conditions across these outcomes. A disease cluster driven by cardiometabolic conditions was consistently associated with poorer brain health across all outcomes. Disease clusters driven by respiratory, mental health and other conditions showed less consistent associations.
Multimorbidity was strongly associated with poorer brain health, particularly within the cardiometabolic disease cluster. Given that UK Biobank participants are, on average, healthier than the general population, future studies in more diverse and representative cohorts would be valuable.
多种疾病共存，尤其是疾病集群，与通常在痴呆临床诊断之前出现的神经影像学和认知结果之间的关系仍未得到充分研究。本研究调查了在英国生物银行队列中，多种疾病共存是否与痴呆相关的神经影像学和认知结果有关。
这项横断面研究使用了英国生物银行参与者的数据，这些参与者在2014年至2023年期间接受了影像学评估，且没有包括痴呆在内的神经系统疾病。多种疾病共存被定义为两种或更多长期疾病同时存在，这些疾病是从39种疾病的标准化标准中选取的。潜在类别分析用于识别疾病集群。神经影像学结果通过磁共振成像测量，认知通过测量不同认知领域的七项测试进行评估。多变量线性回归用于评估多种疾病共存和疾病集群与神经影像学和认知结果之间的关联。
总共纳入了43160名参与者（平均[标准差]年龄为64.2[7.7]岁，53.1%为女性）。14339名（33.2%）参与者存在多种疾病共存，这与灰质体积、全脑体积、左侧海马体积减少、脑血管病变增加以及特定领域认知功能降低有关。在这些结果中，随着多种疾病共存情况数量的增加，观察到了强烈的剂量反应关系。由心脏代谢疾病驱动的疾病集群在所有结果中始终与较差的脑健康相关。由呼吸系统疾病、心理健康和其他疾病驱动的疾病集群显示出的关联不太一致。
多种疾病共存与较差的脑健康密切相关，特别是在心脏代谢疾病集群中。鉴于英国生物银行的参与者平均而言比一般人群更健康，未来在更多样化和更具代表性的队列中进行研究将很有价值。
