Higher plasma β-synuclein indicates early synaptic degeneration in Alzheimer's disease

INTRODUCTION

β-Synuclein is an emerging synaptic blood biomarker for Alzheimer's disease (AD) but differences in β-synuclein levels in preclinical AD and its association with amyloid and tau pathology have not yet been studied.

METHODS

We measured plasma β-synuclein levels in cognitively unimpaired individuals with positive Aβ-PET (i.e., preclinical AD, N = 48) or negative Aβ-PET (N = 61), Aβ-positive patients with mild cognitive impairment (MCI, N = 36), and Aβ-positive AD dementia (N = 85). Amyloid (A) and tau (T) pathology were assessed by [18 F]flutemetamol and [18 F]RO948 PET.

RESULTS

Plasma β-synuclein levels were higher in preclinical AD and even higher in MCI and AD dementia. Stratification according to amyloid/tau pathology revealed higher β-synuclein in A+ T- and A+ T+ subjects compared with A- T- . Plasma β-synuclein levels were related to tau and Aβ pathology and associated with temporal cortical thinning and cognitive impairment.

DISCUSSION

Our data indicate that plasma β-synuclein might track synaptic dysfunction, even during the preclinical stages of AD.

HIGHLIGHTS

Plasma β-synuclein is already higher in preclinical AD. Plasma β-synuclein is higher in MCI and AD dementia than in preclinical AD. Aβ- and tau-PET SUVRs are associated with plasma β-synuclein levels. Plasma β-synuclein is already higher in tau-PET negative subjects. Plasma β-synuclein is related to temporal cortical atrophy and cognitive impairment.

Amyloid-β PET in Alzheimer's disease: A systematic review and Bayesian meta-analysis

BACKGROUND

In recent years, longitudinal studies of Alzheimer's disease (AD) have been successively concluded. Our aim is to determine the efficacy of amyloid-β (Aβ) PET in diagnosing AD and early prediction of mild cognitive impairment (MCI) converting to AD. By pooling studies from different centers to explore in-depth whether diagnostic performance varies by population type, radiotracer type, and diagnostic approach, thus providing a more comprehensive theoretical basis for the subsequent widespread application of Aβ PET in the clinical setting.

METHODS

Relevant studies were searched through PubMed. The pooled sensitivities, specificities, DOR, and the summary ROC curve were obtained based on a Bayesian random-effects model.

RESULTS

Forty-eight studies, including 5967 patients, were included. Overall, the pooled sensitivity, specificity, DOR, and AUC of Aβ PET for diagnosing AD were 0.90, 0.80, 35.68, and 0.91, respectively. Subgroup analysis showed that Aβ PET had high sensitivity (0.91) and specificity (0.81) for differentiating AD from normal controls but very poor specificity (0.49) for determining AD from MCI. The pooled sensitivity and specificity were 0.84 and 0.62, respectively, for predicting the conversion of MCI to AD. The differences in diagnostic efficacy between visual assessment and quantitative analysis and between ¹¹ C-PIB PET and ¹⁸ F-florbetapir PET were insignificant.

CONCLUSIONS

The overall performance of Aβ PET in diagnosing AD is favorable, but the differentiation between MCI and AD patients should consider that some MCI may be at risk of conversion to AD and may be misdiagnosed. A multimodal diagnostic approach and machine learning analysis may be effective in improving diagnostic accuracy.

Relationship Between Body Mass Index, ApoE4 Status, and PET-Based Amyloid and Neurodegeneration Markers in Amyloid-Positive Subjects with Normal Cognition or Mild Cognitive Impairment

Body weight loss in late-life is known to occur at a very early stage of Alzheimer's disease (AD). Apolipoprotein E4 (ApoE4) represents a major genetic risk factor for AD and is linked to an increased cortical amyloid-β (Aβ) accumulation. Since the relationship between body weight, ApoE4, and AD pathology is poorly investigated, we aimed to evaluate whether ApoE4 allelic status modifies the association of body mass index (BMI) with markers of AD pathology. A total of 368 Aβ-positive cognitively healthy or mild cognitive impaired subjects had undergone [18F]-AV45-PET, [18F]-FDG-PET, and T1w-MRI examinations. Composite cortical [18F]-AV45 uptake and [18F]-FDG uptake in posterior cingulate cortex were calculated as surrogates of cortical Aβ load and glucose metabolism, respectively. Multiple linear regressions were performed to assess the relationships between these PET biomarkers with BMI, present cognitive performance, and cognitive changes over time. Multivariate analysis of covariance was conducted to test for statistical differences between ApoE4/BMI categories on the PET markers and cognitive scores. In carriers of the ApoE4 allele only, BMI was inversely associated with cortical amlyoid load (β= -0.193, p < 0.005) and recent cognitive decline (β= -0.209, p < 0.05), and positively associated with cortical glucose metabolism in an AD-vulnerable region (β= 0.145, p < 0.05). ApoE4/BMI category analyses demonstrated lower Aβ load, higher posterior cingulate glucose metabolism, improved cognitive performance, and lower progression of cognitive decline in obese ApoE4 carriers. The effect of ApoE4 in promoting the accumulation of cortical amyoid, which may itself be a driver for weight loss, may be moderated by altering leptin signaling in the hypothalamus.