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淀粉样蛋白与神经退行性变生物标志物状态之间以及向痴呆症转变的速率:一项基于人群的纵向队列研究。

Transition rates between amyloid and neurodegeneration biomarker states and to dementia: a population-based, longitudinal cohort study.

作者信息

Jack Clifford R, Therneau Terry M, Wiste Heather J, Weigand Stephen D, Knopman David S, Lowe Val J, Mielke Michelle M, Vemuri Prashanthi, Roberts Rosebud O, Machulda Mary M, Senjem Matthew L, Gunter Jeffrey L, Rocca Walter A, Petersen Ronald C

机构信息

Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.

Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA.

出版信息

Lancet Neurol. 2016 Jan;15(1):56-64. doi: 10.1016/S1474-4422(15)00323-3. Epub 2015 Nov 18.

Abstract

BACKGROUND

In a 2014 cross-sectional analysis, we showed that amyloid and neurodegeneration biomarker states in participants with no clinical impairment varied greatly with age, suggesting dynamic within-person processes. In this longitudinal study, we aimed to estimate rates of transition from a less to a more abnormal biomarker state by age in individuals without dementia, as well as to assess rates of transition to dementia from an abnormal state.

METHODS

Participants from the Mayo Clinic Study of Aging (Olmsted County, MN, USA) without dementia at baseline were included in this study, a subset of whom agreed to multimodality imaging. Amyloid PET (with (11)C-Pittsburgh compound B) was used to classify individuals as amyloid positive (A(+)) or negative (A(-)). (18)F-fluorodeoxyglucose ((18)F-FDG)-PET and MRI were used to classify individuals as neurodegeneration positive (N(+)) or negative (N(-)). We used all observations, including those from participants who did not have imaging results, to construct a multistate Markov model to estimate four different age-specific biomarker state transition rates: A(-)N(-) to A(+)N(-); A(-)N(-) to A(-)N(+) (suspected non-Alzheimer's pathology); A(+)N(-) to A(+)N(+); and A(-)N(+) to A(+)N(+). We also estimated two age-specific rates to dementia: A(+)N(+) to dementia and A(-)N(+) to dementia. Using these state-to-state transition rates, we estimated biomarker state frequencies by age.

FINDINGS

At baseline (between Nov 29, 2004, to March 7, 2015), 4049 participants did not have dementia (3512 [87%] were clinically normal and 537 [13%] had mild cognitive impairment). 1541 individuals underwent imaging between March 28, 2006, to April 30, 2015. Transition rates were low at age 50 years and, with one exception, exponentially increased with age. At age 85 years compared with age 65 years, the rate was nearly 11-times higher (17.2 vs 1.6 per 100 person-years) for the transition from A(-)N(-) to A(-)N(+), three-times higher (20.8 vs 6.1) for A(+)N(-) to A(+)N(+), and five-times higher (13.2 vs 2.6) for A(-)N(+) to A(+)N(+). The rate of transition was also increased at age 85 years compared with age 65 years for A(+)N(+) to dementia (7.0 vs 0.8) and for A(-)N(+) to dementia (1.7 vs 0.6). The one exception to an exponential increase with age was the transition rate from A(-)N(-) to A(+)N(-), which increased from 4.0 transitions per 100 person-years at age 65 years to 6.9 transitions per 100 person-years at age 75 and then plateaued beyond that age. Estimated biomarker frequencies by age from the multistate model were similar to cross-sectional biomarker frequencies.

INTERPRETATION

Our transition rates suggest that brain ageing is a nearly inevitable acceleration toward worse biomarker and clinical states. The one exception is the transition to amyloidosis without neurodegeneration, which is most dynamic from age 60 years to 70 years and then plateaus beyond that age. We found that simple transition rates can explain complex, highly interdependent biomarker state frequencies in our population.

FUNDING

National Institute on Aging, Alexander Family Professorship of Alzheimer's Disease Research, the GHR Foundation.

摘要

背景

在2014年的一项横断面分析中,我们发现,在无临床损伤的参与者中,淀粉样蛋白和神经退行性变生物标志物状态随年龄变化很大,提示存在动态的个体内过程。在这项纵向研究中,我们旨在估计无痴呆个体中生物标志物状态从较正常向更异常转变的年龄相关发生率,以及评估从异常状态转变为痴呆的发生率。

方法

本研究纳入了美国明尼苏达州奥尔姆斯特德县梅奥诊所衰老研究中基线时无痴呆的参与者,其中一部分同意接受多模态成像检查。淀粉样蛋白PET(使用(11)C-匹兹堡化合物B)用于将个体分类为淀粉样蛋白阳性(A(+))或阴性(A(-))。(18)F-氟脱氧葡萄糖((18)F-FDG)-PET和MRI用于将个体分类为神经退行性变阳性(N(+))或阴性(N(-))。我们利用所有观察结果,包括来自未进行成像检查参与者的结果,构建一个多状态马尔可夫模型,以估计四种不同的年龄特异性生物标志物状态转变率:A(-)N(-)至A(+)N(-);A(-)N(-)至A(-)N(+)(疑似非阿尔茨海默病病理);A(+)N(-)至A(+)N(+);以及A(-)N(+)至A(+)N(+)。我们还估计了两种年龄特异性的痴呆发生率:A(+)N(+)至痴呆和A(-)N(+)至痴呆。利用这些状态间转变率,我们按年龄估计了生物标志物状态频率。

结果

在基线时(2004年11月29日至2015年3月7日之间),4049名参与者无痴呆(3512名[87%]临床正常,537名[13%]有轻度认知障碍)。1541名个体在2006年3月28日至2015年4月30日之间接受了成像检查。50岁时转变率较低,且除一项外,均随年龄呈指数增加。与65岁相比,85岁时从A(-)N(-)至A(-)N(+)的转变率高出近11倍(每100人年17.2次对1.6次),从A(+)N(-)至A(+)N(+)的转变率高出3倍(20.8次对6.1次),从A(-)N(+)至A(+)N(+)的转变率高出5倍(13.2次对2.6次)。与65岁相比,85岁时A(+)N(+)至痴呆(7.0次对0.8次)和A(-)N(+)至痴呆(1.7次对0.6次)的转变率也有所增加。随年龄呈指数增加的唯一例外是从A(-)N(-)至A(+)N(-)的转变率,该转变率从65岁时的每100人年4.0次增加到75岁时的每100人年6.9次,此后趋于平稳。多状态模型按年龄估计的生物标志物频率与横断面生物标志物频率相似。

解读

我们的转变率表明,大脑老化几乎不可避免地加速向更差的生物标志物和临床状态发展。唯一的例外是向无神经退行性变的淀粉样变性转变,这种转变在60岁至70岁之间最为活跃,此后趋于平稳。我们发现,简单的转变率可以解释我们研究人群中复杂的、高度相互依存的生物标志物状态频率。

资助

美国国立衰老研究所、亚历山大家族阿尔茨海默病研究教授职位、GHR基金会。

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