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Early markers are needed for more effective prevention of Alzheimers disease. We previously showed that individuals with Alzheimers disease have decreased plasma DYRK1A levels compared to controls. We assessed DYRK1A in the plasma of cognitively healthy elderly volunteers, individuals with either Alzheimers disease (AD), tauopathies or Down syndrome (DS), and in lymphoblastoids from individuals with DS. DYRK1A levels were inversely correlated with brain amyloid β burden in asymptomatic elderly individuals and AD patients. Low DYRK1A levels were also detected in patients with tauopathies. Individuals with DS had higher DYRK1A levels than controls, although levels were lower in individuals with DS and with dementia. These data suggest that plasma DYRK1A levels could be used for early detection of at risk individuals of AD and for early detection of AD. We hypothesize that lack of increase of DYRK1A at middle age (40-50 years) could be a warning before the cognitive decline, reflecting increased risk for AD.

IntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.

ObjectiveTo estimate the prevalence of amyloid positivity, defined by positron emission tomography (PET)/cerebrospinal fluid (CSF) biomarkers and/or neuropathological examination, in primary progressive aphasia (PPA) variants.MethodsWe conducted a meta-analysis with individual participant data from 1,251 patients diagnosed with PPA (including logopenic [lvPPA, n = 443], nonfluent [nfvPPA, n = 333], semantic [svPPA, n = 401], and mixed/unclassifiable [n = 74] variants of PPA) from 36 centers, with a measure of amyloid-β pathology (CSF [n = 600], PET [n = 366], and/or autopsy [n = 378]) available. The estimated prevalence of amyloid positivity according to PPA variant, age, and apolipoprotein E (ApoE) ε4 status was determined using generalized estimating equation models.ResultsAmyloid-β positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p

Background: Iron accumulates in the brain during aging and is the focus of intensive research as an abnormal load, particularly in Deep Gray Matter (DGM), is related to neurodegeneration. Magnetic Resonance Imaging (MRI) metrics such as Quantitative Susceptibility Mapping (QSM) and apparent transverse relaxation rate R 2 * can be used to follow up iron in vivo. While the influence of age and sex on iron levels has already been reported, a careful consideration of neuronal risk factors, as well as for an enhanced sensitivity, is needed to define the normal evolution. Methods: QSM and R 2 * at ultra-high field MRI are used to study iron in DGM using a carefully-characterized cohort of the healthy aging brain (SENIOR). Seventy-seven cognitively healthy elders (from 54 to 78 y/o) with clinical, biology, genetics, and cardiovascular risk factors careful evaluation. Differences linked with age, sex, cardiovascular risk factors and weight are studied. Results: Age and sex have an influence on the brain iron deposition measured by QSM and R 2 * in a context of normal aging, without appearance of a pathological neurodegenerative process. Iron deposition shows higher values in the caudate and the putamen in older participants. Female participants present a higher level of iron in the amygdala, and males in the thalamus. Female participants also present differences in the accumbens, caudate and hippocampus when evaluating the joint age and sex effect. Participants with higher cardiovascular risk factors showed higher values of the iron, even without any impairment in their cognitive capability. An overweight is related with a higher iron load in the putamen for QSM and R 2 * in female participants. We controlled that these modifications of iron deposition are not related to a specific profile in the genotype of ApoE loci. Conclusions: Establishing baseline values of QSM and R 2 * as iron probes in the context of aging is essential to determine differences in the process of neurodegeneration. Age and sex of participants are important factors that affect brain iron normal values. On the other hand, the presence of cardiovascular risk factors, which can be associated with age related diseases, can also potentially be linked with the iron deposition in the brain. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Typical Alzheimer's disease (AD) and limbic‐predominant age‐related TAR DNA‐binding protein 43 (TDP‐43) encephalopathy (LATE) are two neurodegenerative diseases that present with a similar initial amnestic clinical phenotype but are associated with distinct proteinopathies. METHODS: We investigated white matter (WM) fiber bundle alterations, using fixel‐based analysis, a state‐of‐the‐art diffusion magnetic resonance imaging model, in early AD, presumed LATE, and controls. We also investigated regional cortical atrophy. RESULTS: Both amnestic AD and presumed LATE patients exhibited WM alterations in tracts of the temporal and limbic lobes and in callosal fibers connecting superior frontal gyri. In addition, presumed LATE patients showed alterations in callosal fibers connecting the middle frontal gyri and in the cerebello–thalamo–cortical tract. Cortical thickness was reduced in regions connected by the most altered tracts. DISCUSSION: These findings, the first to describe WM fiber bundle alterations in presumed LATE, are consistent with results on cortical atrophy and with the staging system of tau or TDP‐43 accumulation. Highlights: Fixel‐based analysis revealed white matter (WM) fiber bundle alterations in presumed limbic‐predominant age‐related TAR DNA‐binding protein 43 encephalopathy (LATE) patients identified by isolated episodic/limbic amnesia, the absence of positive Alzheimer's disease (AD) biomarkers, and no other neurological diagnosis after 2 years of follow‐up.Presumed LATE and amnestic AD shared similar patterns of WM alterations in fiber bundles of the limbic and temporal lobes, in congruence with their similar limbic cognitive phenotype.Presumed LATE differed from AD by the alteration of the callosal fibers connecting the middle frontal gyri and of the cerebello–thalamo–cortical tract.WM fiber bundle alterations were consistent with results on regional cortical atrophy.The different anatomical patterns of WM degeneration could provide information on the propagation pathways of distinct proteinopathies. [ABSTRACT FROM AUTHOR]

Introduction: Recent evidence suggests the blood-to-brain influx rate (K1) in TSPO PET imaging as a promising biomarker of blood-brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF). Methods: The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test-retest dataset of [18F]DPA714 scans. Results: Comparison with standard kinetic methodology showed good-toexcellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03-0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans. Discussion: This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers' unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal. [ABSTRACT FROM AUTHOR]

Among opioids, buprenorphine presents a favorable safety profile with a limited risk of respiratory depression. However, fatalities have been reported when buprenorphine is combined to a benzodiazepine. Potentiation of buprenorphine interaction with opioid receptors (ORs) with benzodiazepines, and/or vice versa, is hypothesized to explain this drug-drug interaction (DDI). The mutual DDI between buprenorphine and benzodiazepines was investigated at the neuroreceptor level in nonhuman primates (n = 4 individuals) using brain PET imaging and kinetic modelling. The binding potential (BPND) of benzodiazepine receptor (BzR) was assessed using 11C-flumazenil PET imaging before and after administration of buprenorphine (0.2 mg, i.v.). Moreover, the brain kinetics and receptor binding of buprenorphine were investigated in the same individuals using 11C-buprenorphine PET imaging before and after administration of diazepam (10 mg, i.v.). Outcome parameters were compared using a two-way ANOVA. Buprenorphine did not impact the plasma nor brain kinetics of 11C-flumazenil. 11C-flumazenil BPND was unchanged following buprenorphine exposure, in any brain region (p > 0.05). Similarly, diazepam did not impact the plasma or brain kinetics of 11C-buprenorphine. 11C-buprenorphine volume of distribution (V T) was unchanged following diazepam exposure, in any brain region (p > 0.05). To conclude, our PET imaging findings do not support a neuropharmacokinetic or neuroreceptor-related mechanism of the buprenorphine/benzodiazepine interaction. [ABSTRACT FROM AUTHOR]