Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 Mar;72(3):316-24.
doi: 10.1001/jamaneurol.2014.3314.

Associations between biomarkers and age in the presenilin 1 E280A autosomal dominant Alzheimer disease kindred: a cross-sectional study

Affiliations

Associations between biomarkers and age in the presenilin 1 E280A autosomal dominant Alzheimer disease kindred: a cross-sectional study

Adam S Fleisher et al. JAMA Neurol. 2015 Mar.

Abstract

Importance: Age-associated changes in brain imaging and fluid biomarkers are characterized and compared in presenilin 1 (PSEN1)E280A mutation carriers and noncarriers from the world's largest known autosomal dominant Alzheimer disease (AD) kindred.

Objective: To characterize and compare age-associated changes in brain imaging and fluid biomarkers in PSEN1 E280A mutation carriers and noncarriers.

Design, setting, and participants: Cross-sectional measures of 18F-florbetapir positron emission tomography, 18F-fludeoxyglucose positron emission tomography, structural magnetic resonance imaging, cerebrospinal fluid (CSF), and plasma biomarkers of AD were assessed from 54 PSEN1 E280A kindred members (age range, 20-59 years).

Main outcomes and measures: We used brain mapping algorithms to compare regional cerebral metabolic rates for glucose and gray matter volumes in cognitively unimpaired mutation carriers and noncarriers. We used regression analyses to characterize associations between age and the mean cortical to pontine 18F-florbetapir standard uptake value ratios, precuneus cerebral metabolic rates for glucose, hippocampal gray matter volume, CSF Aβ1-42, total tau and phosphorylated tau181, and plasma Aβ measurements. Age at onset of progressive biomarker changes that distinguish carriers from noncarriers was estimated using best-fitting regression models.

Results: Compared with noncarriers, cognitively unimpaired mutation carriers had significantly lower precuneus cerebral metabolic rates for glucose, smaller hippocampal volume, lower CSF Aβ1-42, higher CSF total tau and phosphorylated tau181, and higher plasma Aβ1-42 measurements. Sequential changes in biomarkers were seen at age 20 years (95% CI, 14-24 years) for CSF Aβ1-42, age 16 years (95% CI, 11-24 years) for the mean cortical 18F-florbetapir standard uptake value ratio, age 15 years (95% CI, 10-24 years) for precuneus cerebral metabolic rate for glucose, age 15 years (95% CI, 7-20 years) for CSF total tau, age 13 years (95% CI, 8-19 years) for phosphorylated tau181, and age 6 years (95% CI, 1-10 years) for hippocampal volume, with cognitive decline up to 6 years before the kindred's estimated median age of 44 years (95% CI, 43-45 years) at mild cognitive impairment diagnosis. No age-associated findings were seen in plasma Aβ1-42 or Aβ1-40.

Conclusions and relevance: This cross-sectional study provides additional information about the course of different AD biomarkers in the preclinical and clinical stages of autosomal dominant AD.

PubMed Disclaimer

Figures

Figure 1
Figure 1. Biomarker Measure Associations With Age
Shown are age-associated biomarker curves for mutation noncarriers and carriers. Some data points were withheld to protect individual identities associated with age. CDR indicates Clinical Dementia Rating; CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; CSF, cerebrospinal fluid; MMSE, Mini-Mental State Examination; PET CMRgl, positron emission tomography precuneous cerebral metabolic rate for glucose; and SUVR, mean standardized uptake value ratio (previously reported).
Figure 2
Figure 2. Voxelwise Comparison of 18F-fludeoxyglucose Positron Emission Tomography (PET)–Measured Cerebral Metabolic Rate for Glucose (CMRgl) and Volumetric Magnetic Resonance (MR) Imaging–Measured Regional Gray Matter in Unimpaired PSEN1 E280A Carriers and Noncarriers
Shown are group comparisons of unimpaired mutation carriers with age-matched noncarriers. A, Reduced 18F-fludeoxyglucose PET CMRgl in cognitively unimpaired mutation carriers vs noncarriers. B, Magnetic resonance imaging gray matter loss in cognitively unimpaired mutation carriers vs noncarriers.
Figure 3
Figure 3. Biomarker Comparisons Between Unimpaired Carriers and Noncarriers
Shown are between-group cross-sectional comparisons between unimpaired PSEN1 E280A mutation carriers vs noncarriers. Significant differences are seen in cerebrospinal fluid (CSF) Aβ1-42, amyloid positron emission tomography (PET) (18F-florbetapir standardized uptake value ratio [SUVR]), CSF total tau, and 18F-fludeoxyglucose PET precuneus cerebral metabolic rate for glucose (CMRgl) but not in bilateral standardized hippocampal volume (P < .05).
Figure 4
Figure 4. Age and Biomarker Associations and Comparison of Age at Onset of Biomarker Changes
Shown are cognitively unimpaired mutation carrier standardized z score curves from zero to one for cerebrospinal fluid (CSF) Aβ1-42, amyloid positron emission tomography (PET) (18F-florbetapir standardized uptake value ratio [SUVR]), CSF total tau, 18F-fludeoxyglucose PET precuneus cerebral metabolic rate for glucose (CMRgl), bilateral standardized hippocampal volume, and memory (Consortium to Establish a Registry for Alzheimer’s Disease [CERAD] word list delayed recall). The age at significant difference from mutation noncarriers is marked with a circle for each respective biomarker. MCI indicates mild cognitive impairment.

References

    1. Bateman RJ, Xiong C, Benzinger TL, et al. Dominantly Inherited Alzheimer Network. Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med. 2012;367(9):795–804. - PMC - PubMed
    1. Reiman EM, Langbaum JB, Fleisher AS, et al. Alzheimer’s Prevention Initiative: a plan to accelerate the evaluation of presymptomatic treatments. J Alzheimers Dis. 2011;26(suppl 3):321–329. - PMC - PubMed
    1. Jack CR, Jr, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12(2):207–216. - PMC - PubMed
    1. Sperling RA, Aisen PS, Beckett LA, et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging–Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):280–292. - PMC - PubMed
    1. Fleisher AS, Chen K, Quiroz YT, et al. Florbetapir PET analysis of amyloid-β deposition in the presenilin 1 E280A autosomal dominant Alzheimer’s disease kindred: a cross-sectional study. Lancet Neurol. 2012;11(12):1057–1065. - PMC - PubMed

Publication types

MeSH terms

Supplementary concepts

LinkOut - more resources