Applicability of in vivo staging of regional amyloid burden in a cognitively normal cohort with subjective memory complaints: the INSIGHT-preAD study.

BACKGROUND:Current methods of amyloid PET interpretation based on the binary classification of global amyloid signal fail to identify early phases of amyloid deposition. A recent analysis of 18F-florbetapir PET data from the Alzheimer's disease Neuroimaging Initiative cohort suggested a hierarchical four-stage model of regional amyloid deposition that resembles neuropathologic estimates and can be used to stage an individual's amyloid burden in vivo. Here, we evaluated the validity of this in vivo amyloid staging model in an independent cohort of older people with subjective memory complaints (SMC). We further examined its potential association with subtle cognitive impairments in this population at elevated risk for Alzheimer's disease (AD). METHODS:The monocentric INSIGHT-preAD cohort includes 318 cognitively intact older individuals with SMC. All individuals underwent 18F-florbetapir PET scanning and extensive neuropsychological testing. We projected the regional amyloid uptake signal into the previously proposed hierarchical staging model of in vivo amyloid progression. We determined the adherence to this model across all cases and tested the association between increasing in vivo amyloid stage and cognitive performance using ANCOVA models. RESULTS:In total, 156 participants (49%) showed evidence of regional amyloid deposition, and all but 2 of these (99%) adhered to the hierarchical regional pattern implied by the in vivo amyloid progression model. According to a conventional binary classification based on global signal (SUVRCereb = 1.10), individuals in stages III and IV were classified as amyloid-positive (except one in stage III), but 99% of individuals in stage I and even 28% of individuals in stage II were classified as amyloid-negative. Neither in vivo amyloid stage nor conventional binary amyloid status was significantly associated with cognitive performance in this preclinical cohort. CONCLUSIONS:The proposed hierarchical staging scheme of PET-evidenced amyloid deposition generalizes well to data from an independent cohort of older people at elevated risk for AD. Future studies will determine the prognostic value of the staging approach for predicting longitudinal cognitive decline in older individuals at increased risk for AD

Association of brain network dynamics with plasma biomarkers in subjective memory complainers

Using a single integrated analysis, we examined the relationship between brain networks and molecular pathways in a cohort of elderly individuals at risk for Alzheimer's disease. In 205 subjective memory complainers (124 females, mean age: 75.7 ± 3.4), individual functional connectome was computed for a total of 3081 functional connections (set A) and 6 core plasma biomarkers of Alzheimer's disease (set B) were assessed. Partial least squares correlation analysis identified one dimension of population covariation between the 2 sets (p < 0.006), which we named bioneural mode. Five core plasma biomarkers and 190 functional connections presented bootstrap ratios greater than the critical value |1.96|. T-tau protein showed a trend toward significance (bootstrap resampling = 1.64). The salience, the language, the visuospatial, and the default mode networks were the strongest significant networks. We detected a strong association between network dynamics and core pathophysiological blood biomarkers. Innovative composite biomarkers, such as the bioneural mode, are promising to provide outcomes and better inform drug development and clinical practice for neurodegenerative diseases

Plasma β-secretase1 concentrations correlate with basal forebrain atrophy and neurodegeneration in cognitively healthy individuals at risk for AD

BACKGROUND: Increased β-secretase 1 (BACE1) protein concentration, in body fluids, is a candidate biomarker of Alzheimer's disease (AD).We reported that plasma BACE1 protein concentrations are associated with the levels of brain amyloidβ (Αβ) accumulation in cognitively healthy individuals with subjective memory complaint (SMC). METHODS: In 302 individuals from the same cohort, we investigated the cross-sectional and longitudinal association between plasma BACE1 protein concentrations and AD biomarkers of neurodegeneration (plasma t-tau and Neurofilament light chain (NfL), fluorodeoxyglucose-positron emission tomography (FDG-PET), brain volumes in the basal forebrain [BF], hippocampus, and entorhinal cortex). RESULTS: We report a positive longitudinal correlation of BACE1 with both NfL and t-tau, as well as a correlation between annual BACE1 changes and bi-annual reduction of BF volume. We show a positive association between BACE1 and FDG-PET signal at baseline. CONCLUSIONS: The association between plasma BACE1 protein concentrations and BF atrophy we found in cognitively healthy individuals with SMC corroborates translational studies, suggesting a role of BACE1 in neurodegeneration

Age and sex impact plasma NFL and t-Tau trajectories in individuals with subjective memory complaints: a 3-year follow-up study

BACKGROUND: Plasma neurofilament light (NFL) and total Tau (t-Tau) proteins are candidate biomarkers for early stages of Alzheimer's disease (AD). The impact of biological factors on their plasma concentrations in individuals with subjective memory complaints (SMC) has been poorly explored. We longitudinally investigate the effect of sex, age, APOE ε4 allele, comorbidities, brain amyloid-β (Aβ) burden, and cognitive scores on plasma NFL and t-Tau concentrations in cognitively healthy individuals with SMC, a condition associated with AD development. METHODS: Three hundred sixteen and 79 individuals, respectively, have baseline and three-time point assessments (at baseline, 1-year, and 3-year follow-up) of the two biomarkers. Plasma biomarkers were measured with an ultrasensitive assay in a mono-center cohort (INSIGHT-preAD study). RESULTS: We show an effect of age on plasma NFL, with women having a higher increase of plasma t-Tau concentrations compared to men, over time. The APOE ε4 allele does not affect the biomarker concentrations while plasma vitamin B12 deficiency is associated with higher plasma t-Tau concentrations. Both biomarkers are correlated and increase over time. Baseline NFL is related to the rate of Aβ deposition at 2-year follow-up in the left-posterior cingulate and the inferior parietal gyri. Baseline plasma NFL and the rate of change of plasma t-Tau are inversely associated with cognitive score. CONCLUSION: We find that plasma NFL and t-Tau longitudinal trajectories are affected by age and female sex, respectively, in SMC individuals. Exploring the influence of biological variables on AD biomarkers is crucial for their clinical validation in blood

Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults

The accumulation of amyloid plaques is one of the earliest pathological changes in Alzheimer’s disease (AD) and may occur 20 years before the onset of symptoms. Examining associations between amyloid pathology and other early brain changes is critical for understanding the pathophysiological underpinnings of AD. Alterations in gray matter networks might already start at early preclinical stages of AD. In this study, we examined the regional relationship between amyloid aggregation measured with positron emission tomography (PET) and gray matter network measures in elderly subjects with subjective memory complaints. Single-subject gray matter networks were extracted from T1-weigthed structural MRI in cognitively normal subjects (n = 318, mean age 76.1 ± 3.5, 64% female, 28% amyloid positive). Degree, clustering, path length and small world properties were computed. Global and regional amyloid load was determined using [18F]-Florbetapir PET. Associations between standardized uptake value ratio (SUVr) values and network measures were examined using linear regression models. We found that higher global SUVr was associated with lower clustering (β = −0.12, p < 0.05), and small world values (β = −0.16, p < 0.01). Associations were most prominent in orbito- and dorsolateral frontal and parieto-occipital regions. Local SUVr values showed less anatomical variability and did not convey additional information beyond global amyloid burden. In conclusion, we found that in cognitively normal elderly subjects, increased global amyloid pathology is associated with alterations in gray matter networks that are indicative of incipient network breakdown towards AD dementia

MiRNA-15b and miRNA-125b are associated with regional Aβ-PET and FDG-PET uptake in cognitively normal individuals with subjective memory complaints.

There is substantial experimental evidence for dysregulation of several microRNA (miRNA) expression levels in Alzheimer's disease (AD). MiRNAs modulate critical brain intracellular signaling pathways and are associated with AD core pathophysiological mechanisms. First, we conducted a real-time quantitative PCR-based pilot study to identify a set of brain-enriched miRNAs in a monocentric cohort of cognitively normal individuals with subjective memory complaints, a condition associated with increased risk of AD. Second, we investigated the impact of age, sex, and the Apolipoprotein E ε4 (APOE ε4) allele, on the identified miRNA plasma concentrations. In addition, we explored the cross-sectional and longitudinal association of the miRNAs plasma concentrations with regional brain metabolic uptake using amyloid-β (Aβ)-positron emission tomography (Aβ-PET) and 18F-fluorodeoxyglucose-PET (18F-FDG-PET). We identified a set of six brain-enriched miRNAs-miRNA-125b, miRNA-146a, miRNA-15b, miRNA-148a, miRNA-26b, and miRNA-100. Age, sex, and APOE ε4 allele were not associated with individual miRNA abundance. MiRNA-15b concentrations were significantly lower in the Aβ-PET-positive compared to Aβ-PET-negative individuals. Furthermore, we found a positive effect of the miRNA-15b*time interaction on regional metabolic 18F-FDG-PET uptake in the left hippocampus. Plasma miRNA-125b concentrations, as well as the miRNA-125b*time interaction (over a 2-year follow-up), were negatively associated with regional Aβ-PET standard uptake value ratio in the right anterior cingulate cortex. At baseline, we found a significantly negative association between plasma miRNA-125b concentrations and 18F-FDG-PET uptake in specific brain regions. In an asymptomatic at-risk population for AD, we show significant associations between plasma concentrations of miRNA-125b and miRNA-15b with core neuroimaging biomarkers of AD pathophysiology. Our results, coupled with existing experimental evidence, suggest a potential protective anti-Aβ effect of miRNA-15b and a biological link between miRNA-125b and Aβ-independent neurotoxic pathways

Association of plasma YKL-40 with brain amyloid-β levels, memory performance, and sex in subjective memory complainers

Neuroinflammation, a key early pathomechanistic alteration of Alzheimer's disease, may represent either a detrimental or a compensatory mechanism or both (according to the disease stage). YKL-40, a glycoprotein highly expressed in differentiated glial cells, is a candidate biomarker for in vivo tracking neuroinflammation in humans. We performed a longitudinal study in a monocentric cohort of cognitively healthy individuals at risk for Alzheimer's disease exploring whether age, sex, and the apolipoprotein E ε4 allele affect plasma YKL-40 concentrations. We investigated whether YKL-40 is associated with brain amyloid-β (Aβ) deposition, neuronal activity, and neurodegeneration as assessed via neuroimaging biomarkers. Finally, we investigated whether YKL-40 may predict cognitive performance. We found an age-associated increase of YKL-40 and observed that men display higher concentrations than women, indicating a potential sexual dimorphism. Moreover, YKL-40 was positively associated with memory performance and negatively associated with brain Aβ deposition (but not with metabolic signal). Consistent with translational studies, our results suggest a potentially protective effect of glia on incipient brain Aβ accumulation and neuronal homeostasis

Multimorbidity Is Associated with Preclinical Alzheimer’s Disease Neuroimaging Biomarkers

International audienceBackground: Identifying comorbidities that influence preclinical Alzheimer’s disease (AD) can give some insight into the AD early stages trajectories to allow new treatment venues and to guide public health systems to prevent subsequent dementia. Objective: To examine the association of multimorbidity with AD neuroimaging markers in cognitively normal older adults. Methods: This study had a cross-sectional design. Data regarding 14 comorbidities were obtained for all 318 adults aged 70–85 years, recruited from the community to an ongoing prospective monocentric cohort. They underwent standardized neuropsychological and neuroimaging assessment with automated methods that measured hippocampal volumes, white matter hyperintensity volumes, fluorodeoxyglucose positron emission tomography (FDG-PET) standardized uptake values (SUV) in AD signature regions, and amyloid positron emission tomography (amyloid-PET) SUV ratios. Linear regression was used to assess the association of multimorbidity with AD neuroimaging biomarkers. Results: Multimorbidity is signif icantly associated with lower hippocampal volumes (–0.03 ± 0.01; p = 0.012; R2 = 0.017) and lower FDG-PET SUV (–0.027 ± 0.009; p = 0.005; R2 = 0.022), with no association with amyloid deposition (0.001 ± 0.007; p = 0.884; R2 = 0.0001). Taken individually, obesity and excessive alcohol use are associated with lower FDG-PET values, whereas obstructive sleep apnea and mood disorders are related to lower amyloid-PET SUV ratios. Conclusion: Multimorbidity is associated with preclinical AD imaging markers of neurodegeneration, but not with amyloid

Aptamarker prediction of brain amyloid-β status in cognitively normal individuals at risk for Alzheimer's disease.

The traditional approach to biomarker discovery for any pathology has been through hypothesis-based research one candidate at a time. The objective of this study was to develop an agnostic approach for the simultaneous screening of plasma for consistent molecular differences between a group of individuals exhibiting a pathology and a group of healthy individuals. To achieve this, we focused on developing a predictive tool based on plasma for the amount of brain amyloid-β deposition as observed in PET scans. The accumulation of brain amyloid-β (Aβ) plaques is a key risk factor for the development of Alzheimer's disease. A contrast was established between cognitively normal individuals above the age of 70 that differed for the amount of brain amyloid-β observed in PET scans (INSIGHT study group). Positive selection was performed against a pool of plasma from individuals with high brain amyloid and negative selection against a pool of plasma from individuals with low brain amyloid This enriched, selected library was then applied to plasma samples from 11 individuals with high levels of brain amyloid and 11 individuals with low levels of brain Aβ accumulation. Each of these individually selected libraries was then characterized by next generation sequencing, and the relative frequency of 10,000 aptamer sequences that were observed in each selection was screened for ability to explain variation in brain amyloid using sparse partial least squares discriminant analysis. From this analysis a subset of 44 aptamers was defined, and the individual aptamers were synthesized. This subset was applied to plasma samples from 70 cognitively normal individuals all above the age of 70 that differed for brain amyloid deposition. 54 individuals were used as a training set, and 15 as a test set. Three of the 15 individuals in the test set were mis-classified resulting in an overall accuracy of 80% with 86% sensitivity and 75% specificity. The aptamers included in the subset serve directly as biomarkers, thus we have named them Aptamarkers. There are two potential applications of these results: extending the predictive capacity of these aptamers across a broader range of individuals, and/or using the individual aptamers to identify targets through covariance analysis and reverse omics approaches. We are currently expanding applications of the Aptamarker platform to other diseases and target matrices

Aptamarker prediction of brain amyloid-β status in cognitively normal individuals at risk for Alzheimer's disease.

The traditional approach to biomarker discovery for any pathology has been through hypothesis-based research one candidate at a time. The objective of this study was to develop an agnostic approach for the simultaneous screening of plasma for consistent molecular differences between a group of individuals exhibiting a pathology and a group of healthy individuals. To achieve this, we focused on developing a predictive tool based on plasma for the amount of brain amyloid-β deposition as observed in PET scans. The accumulation of brain amyloid-β (Aβ) plaques is a key risk factor for the development of Alzheimer's disease. A contrast was established between cognitively normal individuals above the age of 70 that differed for the amount of brain amyloid-β observed in PET scans (INSIGHT study group). Positive selection was performed against a pool of plasma from individuals with high brain amyloid and negative selection against a pool of plasma from individuals with low brain amyloid This enriched, selected library was then applied to plasma samples from 11 individuals with high levels of brain amyloid and 11 individuals with low levels of brain Aβ accumulation. Each of these individually selected libraries was then characterized by next generation sequencing, and the relative frequency of 10,000 aptamer sequences that were observed in each selection was screened for ability to explain variation in brain amyloid using sparse partial least squares discriminant analysis. From this analysis a subset of 44 aptamers was defined, and the individual aptamers were synthesized. This subset was applied to plasma samples from 70 cognitively normal individuals all above the age of 70 that differed for brain amyloid deposition. 54 individuals were used as a training set, and 15 as a test set. Three of the 15 individuals in the test set were mis-classified resulting in an overall accuracy of 80% with 86% sensitivity and 75% specificity. The aptamers included in the subset serve directly as biomarkers, thus we have named them Aptamarkers. There are two potential applications of these results: extending the predictive capacity of these aptamers across a broader range of individuals, and/or using the individual aptamers to identify targets through covariance analysis and reverse omics approaches. We are currently expanding applications of the Aptamarker platform to other diseases and target matrices