PDF(Pubmed)
Abstract：
UNASSIGNED: Little is known regarding associations of conventional and emerging diseases and their multimorbidity with brain volumes.
UNASSIGNED: This cross-sectional study included 36,647 European ancestry individuals aged 44-81 years with brain magnetic resonance imaging data from UK Biobank. Brain volumes were measured between 02 May 2014 and 31 October 2019. General linear regression models were used to associate 57 individual major diseases with brain volumes. Latent class analysis was used to identify multimorbidity patterns. A multimorbidity score for brain volumes was computed based on the estimates for individual groups of diseases.
UNASSIGNED: Out of 57 major diseases, 16 were associated with smaller volumes of total brain, 14 with smaller volumes of grey matter, and six with smaller hippocampus volumes, and four major diseases were associated with higher white matter hyperintensity (WMH) load after adjustment for all other diseases. The leading contributors to the variance of total brain volume were hypertension (R2=0·0229), dyslipidemia (0·0190), cataract (0·0176), coronary heart disease (0·0107), and diabetes (0·0077). We identified six major multimorbidity patterns and multimorbidity patterns of cardiometabolic disorders (CMD), and CMD-multiple disorders, and metabolic disorders were independently associated with smaller volumes of total brain (β (95% CI): -6·6 (-8·9, -4·3) ml, -7·3 (-10·4, -4·1) ml, and -10·4 (-13·5, -7·3) ml, respectively), grey matter (-7·1 (-8·5, -5·7) ml, -9·0 (-10·9, -7·1) ml, and -11·8 (-13·6, -9·9) ml, respectively), and higher WMH load (0·23 (0·19, 0·27), 0·25 (0·19, 0·30), and 0·33 (0·27, 0·39), respectively) after adjustment for geographic, socioeconomic, and lifestyle factors (all P-values<0·0001). The percentage of the variance of total brain volume explained by multimorbidity patterns, multimorbidity defined by the number of diseases, and multimorbidity score was 1·2%, 3·1%, and 7·2%, respectively. Associations between CMD-multiple disorders pattern, and metabolic disorders pattern and volumes of total brain, grey matter, and WMH were stronger in men than in women. Associations between multimorbidity and brain volumes were stronger in younger than in older individuals.
UNASSIGNED: Besides conventional diseases, we found an association between numerous emerging diseases and smaller brain volumes. CMD-related multimorbidity patterns are associated with smaller brain volumes. Men or younger adults with multimorbidity are more in need of care for promoting brain health. These findings are from an association study and will need confirmation.
UNASSIGNED: The Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075), Science and Technology Program of Guangzhou, China (202,002,020,049).
UNASSIGNED: This cross-sectional study included 36,647 European ancestry individuals aged 44-81 years with brain magnetic resonance imaging data from UK Biobank. Brain volumes were measured between 02 May 2014 and 31 October 2019. General linear regression models were used to associate 57 individual major diseases with brain volumes. Latent class analysis was used to identify multimorbidity patterns. A multimorbidity score for brain volumes was computed based on the estimates for individual groups of diseases.
UNASSIGNED: Out of 57 major diseases, 16 were associated with smaller volumes of total brain, 14 with smaller volumes of grey matter, and six with smaller hippocampus volumes, and four major diseases were associated with higher white matter hyperintensity (WMH) load after adjustment for all other diseases. The leading contributors to the variance of total brain volume were hypertension (R2=0·0229), dyslipidemia (0·0190), cataract (0·0176), coronary heart disease (0·0107), and diabetes (0·0077). We identified six major multimorbidity patterns and multimorbidity patterns of cardiometabolic disorders (CMD), and CMD-multiple disorders, and metabolic disorders were independently associated with smaller volumes of total brain (β (95% CI): -6·6 (-8·9, -4·3) ml, -7·3 (-10·4, -4·1) ml, and -10·4 (-13·5, -7·3) ml, respectively), grey matter (-7·1 (-8·5, -5·7) ml, -9·0 (-10·9, -7·1) ml, and -11·8 (-13·6, -9·9) ml, respectively), and higher WMH load (0·23 (0·19, 0·27), 0·25 (0·19, 0·30), and 0·33 (0·27, 0·39), respectively) after adjustment for geographic, socioeconomic, and lifestyle factors (all P-values<0·0001). The percentage of the variance of total brain volume explained by multimorbidity patterns, multimorbidity defined by the number of diseases, and multimorbidity score was 1·2%, 3·1%, and 7·2%, respectively. Associations between CMD-multiple disorders pattern, and metabolic disorders pattern and volumes of total brain, grey matter, and WMH were stronger in men than in women. Associations between multimorbidity and brain volumes were stronger in younger than in older individuals.
UNASSIGNED: Besides conventional diseases, we found an association between numerous emerging diseases and smaller brain volumes. CMD-related multimorbidity patterns are associated with smaller brain volumes. Men or younger adults with multimorbidity are more in need of care for promoting brain health. These findings are from an association study and will need confirmation.
UNASSIGNED: The Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075), Science and Technology Program of Guangzhou, China (202,002,020,049).
摘要：
未经证实：关于常规和新出现的疾病及其多发病率与脑容量的关联知之甚少。
UNASSIGNED：这项横断面研究包括36,647名44-81岁的欧洲血统个体，其大脑磁共振成像数据来自英国生物库。在2014年5月2日至2019年10月31日期间测量脑体积。使用一般线性回归模型将57种主要疾病与脑体积相关联。潜在类别分析用于鉴定多发病率模式。基于对单个疾病组的估计来计算脑体积的多发病率评分。
未经批准：在57种主要疾病中，16与大脑总量较小有关，14具有较小体积的灰质，六个海马体较小，在调整所有其他疾病后，四种主要疾病与较高的白质高强度（WMH）负荷有关。总脑容量变化的主要原因是高血压(R2=0·0229)，血脂异常（0·0190），白内障（0·0176），冠心病（0·0107），和糖尿病（0·0077）。我们确定了心脏代谢紊乱（CMD）的六种主要多发病模式和多发病模式，和CMD-多发性疾病，代谢紊乱与总脑体积较小独立相关（β（95％CI）：-6·6（-8·9，-4·3）ml，-7·3（-10·4，-4·1）ml，和-10·4（-13·5，-7·3）毫升，分别)，灰质(-7·1(-8·5，-5·7)毫升，-9·0(-10·9,-7·1)ml,和-11·8（-13·6，-9·9）毫升，分别)，和更高的WMH载荷(0·23(0·19，0·27)，0·25（0·19，0·30），和0·33（0·27，0·39），分别)在地理调整后，社会经济,和生活方式因素（所有P值<0.0001）。由多患病模式解释的大脑总体积方差的百分比，由疾病数量定义的多发病率，多症评分为1·2%，3·1%，和7·2%，分别。CMD-多种疾病模式之间的关联，以及整个大脑的代谢紊乱模式和体积，灰质,WMH在男性中比女性强。年轻人的多发病率和脑容量之间的关联比老年人强。
未经授权：除了常规疾病，我们发现许多新出现的疾病与较小的脑容量之间存在关联。CMD相关的多患病模式与较小的脑体积相关。患有多种疾病的男性或年轻成年人更需要护理以促进大脑健康。这些发现来自关联研究，需要确认。
未经批准：眼科国家重点实验室基础研究经费，广州市金融业从业人员健康状况调查项目,中国(Z012014075),广州市科技计划,中国(202,002,020,049)。
UNASSIGNED：这项横断面研究包括36,647名44-81岁的欧洲血统个体，其大脑磁共振成像数据来自英国生物库。在2014年5月2日至2019年10月31日期间测量脑体积。使用一般线性回归模型将57种主要疾病与脑体积相关联。潜在类别分析用于鉴定多发病率模式。基于对单个疾病组的估计来计算脑体积的多发病率评分。
未经批准：在57种主要疾病中，16与大脑总量较小有关，14具有较小体积的灰质，六个海马体较小，在调整所有其他疾病后，四种主要疾病与较高的白质高强度（WMH）负荷有关。总脑容量变化的主要原因是高血压(R2=0·0229)，血脂异常（0·0190），白内障（0·0176），冠心病（0·0107），和糖尿病（0·0077）。我们确定了心脏代谢紊乱（CMD）的六种主要多发病模式和多发病模式，和CMD-多发性疾病，代谢紊乱与总脑体积较小独立相关（β（95％CI）：-6·6（-8·9，-4·3）ml，-7·3（-10·4，-4·1）ml，和-10·4（-13·5，-7·3）毫升，分别)，灰质(-7·1(-8·5，-5·7)毫升，-9·0(-10·9,-7·1)ml,和-11·8（-13·6，-9·9）毫升，分别)，和更高的WMH载荷(0·23(0·19，0·27)，0·25（0·19，0·30），和0·33（0·27，0·39），分别)在地理调整后，社会经济,和生活方式因素（所有P值<0.0001）。由多患病模式解释的大脑总体积方差的百分比，由疾病数量定义的多发病率，多症评分为1·2%，3·1%，和7·2%，分别。CMD-多种疾病模式之间的关联，以及整个大脑的代谢紊乱模式和体积，灰质,WMH在男性中比女性强。年轻人的多发病率和脑容量之间的关联比老年人强。
未经授权：除了常规疾病，我们发现许多新出现的疾病与较小的脑容量之间存在关联。CMD相关的多患病模式与较小的脑体积相关。患有多种疾病的男性或年轻成年人更需要护理以促进大脑健康。这些发现来自关联研究，需要确认。
未经批准：眼科国家重点实验室基础研究经费，广州市金融业从业人员健康状况调查项目,中国(Z012014075),广州市科技计划,中国(202,002,020,049)。
