Importance

The extent to which large-caliber axonal degeneration contributes to Alzheimer disease (AD) progression is unknown. Cerebrospinal fluid (CSF) neurofilament light (NFL) concentration is a general marker of damage to large-caliber myelinated axons.

Objective

To test whether CSF NFL concentration is associated with cognitive decline and imaging evidence of neurodegeneration and white matter change in AD.

Design, setting, and participants

A commercially available immunoassay was used to analyze CSF NFL concentration in a cohort of patients with AD (n = 95) or mild cognitive impairment (MCI) (n = 192) and in cognitively normal individuals (n = 110) from the Alzheimer's Disease Neuroimaging Initiative. The study dates were January 2005 to December 2007. The NFL analysis was performed in November 2014.

Main outcomes and measures

Correlation was investigated among baseline CSF NFL concentration and longitudinal cognitive impairment, white matter change, and regional brain atrophy within each diagnostic group.

Results

Cerebrospinal fluid NFL concentration (median [interquartile range]) was higher in the AD dementia group (1479 [1134-1842] pg/mL), stable MCI group (no progression to AD during follow-up; 1182 [923-1687] pg/mL), and progressive MCI group (MCI with progression to AD dementia during follow-up; 1336 [1061-1693] pg/mL) compared with control participants (1047 [809-1265] pg/mL) (P < .001 for all) and in the AD dementia group compared with the stable MCI group (P = .01). In the MCI group, a higher CSF NFL concentration was associated with faster brain atrophy over time as measured by changes in whole-brain volume (β = -4177, P = .003), ventricular volume (β = 1835, P < .001), and hippocampus volume (β = -54.22, P < .001); faster disease progression as reflected by decreased Mini-Mental State Examination scores (β = -1.077, P < .001) and increased Alzheimer Disease Assessment Scale cognitive subscale scores (β = 2.30, P < .001); and faster white matter intensity change (β = 598.7, P < .001).

Conclusions and relevance

Cerebrospinal fluid NFL concentration is increased by the early clinical stage of AD and is associated with cognitive deterioration and structural brain changes over time. This finding corroborates the contention that degeneration of large-caliber axons is an important feature of AD neurodegeneration.

Background

Cigarette smoking in adults is associated with abnormalities in brain neurobiology. Smoking-induced central nervous system oxidative stress (OxS) is a potential mechanism associated with these abnormalities. The goal of this study was to compare cognitively-normal elders on cerebrospinal fluid (CSF) levels of F2-isoprostane biomarkers of OxS.

Methods

Elders with a lifetime history of smoking (smokers; n=50; 75±5 years of age; 34±28 pack-years; approximately 12% were actively smoking at the time of study) were compared to never-smokers (n=61; 76±6 years of age) on CSF iPF2α-III and 8,12, iso-iPF2α-VI F2-isoprostanes levels. F2-isoprostanes levels were quantitated with HPLC-atmospheric pressure chemical ionization-tandem mass spectrometry. Associations between F2-isoprostanes levels, hippocampal volumes, and cigarette exposure measures were also evaluated.

Results

Smokers showed higher iPF2α-III level than never-smokers. An age×smoking status interaction was observed for 8,12, iso-iPF2α-VI, where smokers demonstrate a significantly greater concentration with increasing age than never-smokers. In smokers only, higher 8,12, iso-iPF2α-VI concentration was associated with smaller hippocampal volume, and greater iPF2α-III level was related to greater pack years.

Conclusions

This is the first study to demonstrate that a history of cigarette smoking in cognitively-normal elders was associated with significantly elevated CSF F2-isoprostane levels and greater age-related increases in F2-isoprostanes, and that higher F2-isoprostane levels in smokers were related to smaller hippocampal volume. These findings provide additional novel evidence that a history of chronic smoking during adulthood is associated with adverse effects on the human brain that are potentially enduring even with extended smoking cessation.

Background

There is epidemiological evidence that cardiovascular risk factors (CVRF) also are risk factors for Alzheimer's disease, but there is limited information on this from neuropathological studies, and even less from in vivo studies. Therefore, we examined the relationship between CVRF and amyloid-β (Aβ) brain burden measured by Pittsburgh Compound B-positron emission tomography (PiB-PET) studies in the Alzheimer's Disease Neuroimaging Initiative.

Methods

Ninety-nine subjects from the Alzheimer's Disease Neuroimaging Initiative cohort who had a PiB-PET study measure, apolipoprotein E genotyping data, and information available on CVRF (body mass index [BMI], systolic blood pressure, diastolic blood pressure [DBP], and cholesterol and fasting glucose test results) were included. Eighty-one subjects also had plasma cortisol, C-reactive protein, and superoxide dismutase 1 measurements. Stepwise regression models were used to assess the relation between the CVRF and the composite PiB-PET score.

Results

The first model included the following as baseline variables: age, clinical diagnosis, number of apolipoprotein ɛ4 alleles, BMI (P = .023), and DBP (P = .012). BMI showed an inverse relation with PiB-PET score, and DBP had a positive relation with PiB-PET score. In the second adjusted model, cortisol plasma levels were also associated with PiB-PET score (P = .004). Systolic blood pressure, cholesterol, or impaired fasting glucose were not found to be associated with PiB-PET values.

Conclusion

In this cross-sectional study, we found an association between Aβ brain burden measured in vivo and DBP and cortisol, indicating a possible link between these CVRF and Aβ burden measured by PiB-PET. These findings highlight the utility of biomarkers to explore potential pathways linking diverse Alzheimer's disease risk factors.

Importance

Cerebrospinal fluid (CSF) and positron emission tomographic (PET) amyloid biomarkers have been proposed for the detection of Alzheimer disease (AD) pathology in living patients and for the tracking of longitudinal changes, but the relation between biomarkers needs further study.

Objective

To determine the association between CSF and PET amyloid biomarkers (cross-sectional and longitudinal measures) and compare the cutoffs for these measures.

Design, setting, and participants

Longitudinal clinical cohort study from 2005 to 2014 including 820 participants with at least 1 florbetapir F-18 (hereafter referred to as simply florbetapir)-PET scan and at least 1 CSF β-amyloid 1-42 (Aβ1-42) sample obtained within 30 days of each other (501 participants had a second PET scan after 2 years, including 150 participants with CSF Aβ1-42 measurements). Data were obtained from the Alzheimer's Disease Neuroimaging Initiative database.

Main outcomes and measures

Four different PET scans processing pipelines from 2 different laboratories were compared. The PET cutoff values were established using a mixture-modeling approach, and different mathematical models were applied to define the association between CSF and PET amyloid measures.

Results

The values of the CSF Aβ1-42 samples and florbetapir-PET scans showed a nonlinear association (R2 = 0.48-0.66), with the strongest association for values in the middle range. The presence of a larger dynamic range of florbetapir-PET scan values in the higher range compared with the CSF Aβ1-42 plateau explained the differences in correlation with cognition (R2 = 0.36 and R2 = 0.25, respectively). The APOE genotype significantly modified the association between both biomarkers. The PET cutoff values derived from an unsupervised classifier converged with previous PET cutoff values and the established CSF Aβ1-42 cutoff levels. There was no association between longitudinal Aβ1-42 levels and standardized uptake value ratios during follow-up.

Conclusions and relevance

The association between both biomarkers is limited to a middle range of values, is modified by the APOE genotype, and is absent for longitudinal changes; 4 different approaches in 2 different platforms converge on similar pathological Aβ cutoff levels; and different pipelines to process PET scans showed correlated but not identical results. Our findings suggest that both biomarkers measure different aspects of AD Aβ pathology.

There are conflicting results regarding how APOE genotype, the strongest genetic risk factor for Alzheimer's disease (AD), influences spatial and longitudinal amyloid-β (Aβ) deposition and its impact on the selection of biomarker cut-points. In our study, we sought to determine the impact of APOE genotype on cross-sectional and longitudinal florbetapir positron emission tomography (PET) amyloid measures and its impact in classification of patients and interpretation of clinical cohort results. We included 1,019 and 1,072 Alzheimer's Disease Neuroimaging Initiative participants with cerebrospinal fluid Aβ1 - 42 and florbetapir PET values, respectively. 623 of these subjects had a second florbetapir PET scans two years after the baseline visit. We evaluated the effect of APOE genotype on Aβ distribution pattern, pathological biomarker cut-points, cross-sectional clinical associations with Aβ load, and longitudinal Aβ deposition rate measured using florbetapir PET scans. 1) APOEɛ4 genotype influences brain amyloid deposition pattern; 2) APOEɛ4 genotype does not modify Aβ biomarker cut-points estimated using unsupervised mixture modeling methods if white matter and brainstem references are used (but not when cerebellum is used as a reference); 3) findings of large differences in Aβ biomarker value differences based on APOE genotype are due to increased probability of having AD neuropathology and are most significant in mild cognitive impairment subjects; and 4) APOE genotype and age (but not gender) were associated with increased Aβ deposition rate. APOEɛ4 carrier status affects rate and location of brain Aβ deposition but does not affect choice of biomarker cut-points if adequate references are selected for florbetapir PET processing.

Objective

We examined agreement and disagreement between 2 biomarkers of β-amyloid (Aβ) deposition (amyloid positron emission tomography [PET] and cerebrospinal fluid [CSF] Aβ1-42 ) in normal aging and dementia in a large multicenter study.

Methods

Concurrently acquired florbetapir PET and CSF Aβ were measured in cognitively normal, mild cognitive impairment (MCI), and Alzheimer's disease participants (n = 374) from the Alzheimer's Disease Neuroimaging Initiative. We also compared Aβ measurements in a separate group with serial CSF measurements over 3.1 ± 0.8 years that preceded a single florbetapir session. Additional biomarker and cognitive data allowed us to further examine profiles of discordant cases.

Results

Florbetapir and CSF Aβ were inversely correlated across all diagnostic groups, and dichotomous measurements were in agreement in 86% of subjects. Among subjects showing the most disagreement, the 2 discordant groups had different profiles: the florbetapir(+) /CSF Aβ(-) group was larger (n = 13) and was made up of only normal and early MCI subjects, whereas the florbetapir(-) /CSF Aβ(+) group was smaller (n = 7) and had poorer cognitive function and higher CSF tau, but no ApoE4 carriers. In the longitudinal sample, we observed both stable longitudinal CSF Aβ trajectories and those actively transitioning from normal to abnormal, but the final CSF Aβ measurements were in good agreement with florbetapir cortical retention.

Interpretation

CSF and amyloid PET measurements of Aβ were consistent in the majority of subjects in the cross-sectional and longitudinal populations. Based on our analysis of discordant subjects, the available evidence did not show that CSF Aβ regularly becomes abnormal prior to fibrillar Aβ accumulation early in the course of disease.

Apolipoprotein E (APOE) ε4 allele is the most important genetic risk factor for Alzheimer's disease (AD) and it is thought to do so by modulating levels of its product, apolipoprotein E (Apo-E), and regulating amyloid-β (Aβ) clearance. However, information on clinical and biomarker correlates of Apo-E proteins is scarce. We examined the relationship of cerebrospinal fluid (CSF) and plasma Apo-E protein levels, and APOE genotype to cognition and AD biomarker changes in 311 AD neuroimaging initiative subjects with CSF Apo-E measurements and 565 subjects with plasma Apo-E measurements. At baseline, higher CSF Apo-E levels were associated with higher total and phosphorylated CSF tau levels. CSF Apo-E levels were associated with longitudinal cognitive decline, MCI conversion to dementia, and gray matter atrophy rate in total tau/Aβ1-42 ratio and APOE genotype-adjusted analyses. In analyses stratified by APOE genotype, our results were only significant in the group without the ε4 allele. Baseline CSF Apo-E levels did not predict longitudinal CSF Aβ or tau changes. Plasma Apo-E levels show a mild correlation with CSF Apo-E levels, but were not associated with longitudinal cognitive and MRI changes. Based on our analyses, we speculate that increased CSF Apo-E2 or -E3 levels might represent a protective response to injury in AD and may have neuroprotective effects by decreasing neuronal damage independent of tau and amyloid deposition in addition to its effects on amyloid clearance.

Background

Recently, tau PET tracers have shown strong associations with clinical outcomes in individuals with cognitive impairment and cognitively unremarkable elderly individuals. flortaucipir PET scans to measure tau deposition in multiple brain areas as the disease progresses. This information needs to be summarized to evaluate disease severity and predict disease progression. We, therefore, sought to develop a machine learning-derived index, SPARE-Tau, which successfully detects pathology in the earliest disease stages and accurately predicts progression compared to a priori-based region of interest approaches (ROI).

Methods

587 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort had flortaucipir scans, structural MRI scans, and an Aβ biomarker test (CSF or florbetapir PET) performed on the same visit. We derived the SPARE-Tau index in a subset of 367 participants. We evaluated associations with clinical measures for CSF p-tau, SPARE-MRI, and flortaucipir PET indices (SPARE-Tau, meta-temporal, and average Braak ROIs). Bootstrapped multivariate adaptive regression splines linear regression analyzed the association between the biomarkers and baseline ADAS-Cog13 scores. Bootstrapped multivariate linear regression models evaluated associations with clinical diagnosis. Cox-hazards and mixed-effects models investigated clinical progression and longitudinal ADAS-Cog13 changes. The Aβ positive cognitively unremarkable participants, not included in the SPARE-Tau training, served as an independent validation group.

Results

Compared to CSF p-tau, meta-temporal, and averaged Braak tau PET ROIs, SPARE-Tau showed the strongest association with baseline ADAS-cog13 scores and diagnosis. SPARE-Tau also presented the strongest association with clinical progression in cognitively unremarkable participants and longitudinal ADAS-Cog13 changes. Results were confirmed in the Aβ+ cognitively unremarkable hold-out sample participants. CSF p-tau showed the weakest cross-sectional associations and longitudinal prediction.

Discussion

Flortaucipir indices showed the strongest clinical association among the studied biomarkers (flortaucipir, florbetapir, structural MRI, and CSF p-tau) and were predictive in the preclinical disease stages. Among the flortaucipir indices, the machine-learning derived SPARE-Tau index was the most sensitive clinical progression biomarker. The combination of different biomarker modalities better predicted cognitive performance.

Importance

The effect of β-amyloid (Aβ) accumulation on regional structural brain changes in early stages of Alzheimer disease (AD) is not well understood.

Objective

To test the hypothesis that the development of Aβ pathology is related to increased regional atrophy in the brains of cognitively normal (CN) persons.

Design, setting, and participants

Longitudinal clinicobiomarker cohort study involving 47 CN control subjects and 15 patients with AD dementia. All participants underwent repeated cerebrospinal fluid Aβ42 and structural magnetic resonance imaging measurements for up to 4 years. Cognitively normal controls were classified using the longitudinal cerebrospinal fluid Aβ42 data and included 13 stable Aβ negative (normal baseline Aβ42 levels, with less than the median reduction over time), 13 declining Aβ negative (normal baseline Aβ42 levels, with greater than the median reduction over time), and 21 Aβ positive (pathologic baseline Aβ42 levels). All 15 patients with AD dementia were Aβ positive.

Main outcomes and measures

Group effects on regional gray matter volumes at baseline and over time, tested by linear mixed-effects models.

Results

Baseline gray matter volumes were similar among the CN Aβ groups, but atrophy rates were increased in frontoparietal regions in the declining Aβ-negative and Aβ-positive groups and in amygdala and temporal regions in the Aβ-positive group. Aβ-positive patients with AD dementia had further increased atrophy rates in hippocampus and temporal and cingulate regions.

Conclusions and relevance

Emerging Aβ pathology is coupled to increased frontoparietal (but not temporal) atrophy rates. Atrophy rates peak early in frontoparietal regions but accelerate in hippocampus, temporal, and cingulate regions as the disease progresses to dementia. Early-stage Aβ pathology may have mild effects on local frontoparietal cortical integrity while effects in temporal regions appear later and accelerate, leading to the atrophy pattern typically seen in AD.

Biomarkers associated with Alzheimer's disease (AD)-like brain atrophy in healthy individuals may identify mechanisms involved in early stage AD. Aside from cerebrospinal fluid (CSF) β-amyloid42 (Aβ42) and tau, no studies have tested associations between CSF proteins and AD-like brain atrophy. We studied 90 healthy elders, who underwent lumbar puncture at baseline, and serial magnetic resonance imaging scans for up to 4 years. We tested statistical effects of baseline CSF proteins (N = 70 proteins related to Aβ42-metabolism, microglial activity, and synaptic/neuronal function) on atrophy rates in 7 AD-related regions. Besides the effects of Aβ42 and phosphorylated tau (P-tau) that were seen in several regions, novel CSF proteins were found to have effects in inferior and middle temporal cortex (including apolipoprotein CIII, apolipoprotein D, and apolipoprotein H). Several proteins (including S100β and matrix metalloproteinase-3) had effects that depended on the presence of brain Aβ pathology, as measured by CSF Aβ42. Other proteins (including P-tau and apolipoprotein D) had effects even after adjusting for CSF Aβ42. The statistical effects in this exploratory study were mild and not significant after correction for multiple comparisons, but some of the identified proteins may be associated with brain atrophy in healthy persons. Proteins interacting with CSF Aβ42 may be related to Aβ brain pathology, whereas proteins associated with atrophy even after adjusting for CSF Aβ42 may be related to Aβ-independent mechanisms.