Bryan J. Neth

Effects of Regular and Long-Acting Insulin on Cognition and Alzheimer’s Disease Biomarkers: A Pilot Clinical Trial

Background: Long acting insulin detemir administered intranasally for three weeks enhanced memory for adults with Alzheimer’s disease dementia (AD) or amnestic mild cognitive impairment (MCI). The investigation of longer-term administration is necessary to determine whether benefits persist, whether they are similar to benefits provided by regular insulin, and whether either form of insulin therapy affects AD biomarkers. Objective: The present study aimed to determine whether four months of treatment with intranasal insulin detemir or regular insulin improves cognition, daily functioning, and AD biomarkers for adults with MCI or AD. Methods: This randomized, double-blind, placebo-controlled trial included an intent-to-treat sample consisting of 36 adults diagnosed with MCI or mild to moderate AD. Participants received placebo (n = 12), 40 IU of insulin detemir (n = 12), or 40 IU of regular insulin (n = 12) daily for four months, administered with a nasal delivery device. A cognitive battery was administered at baseline and after two and four months of treatment. MRI was administered for all participants and lumbar puncture for a subset (n = 20) at baseline and four months. The primary outcome was change from baseline to four months on a memory composite (sum of Z scores for delayed list and story recall). Secondary outcomes included: global cognition (Alzheimer’s Disease Assessment Scale-Cognition), daily functioning (Dementia Severity Rating Scale), MRI volume changes in AD-related regions of interest, and cerebrospinal fluid AD markers. Results: The regular insulin treated group had better memory after two and four months compared with placebo (p < 0.03). No significant effects were observed for the detemir-assigned group compared with the placebo group, or for daily functioning for either group. Regular insulin treatment was associated with preserved volume on MRI. Regular insulin treatment was also associated with reduction in the tau-P181/Aβ42 ratio. Conclusion: Future research is warranted to examine the mechanistic basis of treatment differences, and to further assess the efficacy and safety of intranasal insulin.

Insulin Resistance and Alzheimer’s Disease: Bioenergetic Linkages

Metabolic dysfunction is a well-established feature of Alzheimer’s disease (AD), evidenced by brain glucose hypometabolism that can be observed potentially decades prior to the development of AD symptoms. Furthermore, there is mounting support for an association between metabolic disease and the development of AD and related dementias. Individuals with insulin resistance, type 2 diabetes mellitus (T2D), hyperlipidemia, obesity, or other metabolic disease may have increased risk for the development of AD and similar conditions, such as vascular dementia. This association may in part be due to the systemic mitochondrial dysfunction that is common to these pathologies. Accumulating evidence suggests that mitochondrial dysfunction is a significant feature of AD and may play a fundamental role in its pathogenesis. In fact, aging itself presents a unique challenge due to inherent mitochondrial dysfunction and prevalence of chronic metabolic disease. Despite the progress made in understanding the pathogenesis of AD and in the development of potential therapies, at present we remain without a disease-modifying treatment. In this review, we will discuss insulin resistance as a contributing factor to the pathogenesis of AD, as well as the metabolic and bioenergetic disruptions linking insulin resistance and AD. We will also focus on potential neuroimaging tools for the study of the metabolic dysfunction commonly seen in AD with hopes of developing therapeutic and preventative targets.

Blood-Based Bioenergetic Profiling Reflects Differences in Brain Bioenergetics and Metabolism

Blood-based bioenergetic profiling provides a minimally invasive assessment of mitochondrial health shown to be related to key features of aging. Previous studies show that blood cells recapitulate mitochondrial alterations in the central nervous system under pathological conditions, including the development of Alzheimers disease. In this study of nonhuman primates, we focus on mitochondrial function and bioenergetic capacity assessed by the respirometric profiling of monocytes, platelets, and frontal cortex mitochondria. Our data indicate that differences in the maximal respiratory capacity of brain mitochondria are reflected by CD14+ monocyte maximal respiratory capacity and platelet and monocyte bioenergetic health index. A subset of nonhuman primates also underwent [18F] fluorodeoxyglucose positron emission tomography (FDG-PET) imaging to assess brain glucose metabolism. Our results indicate that platelet respiratory capacity positively correlates to measures of glucose metabolism in multiple brain regions. Altogether, the results of this study provide early evidence that blood-based bioenergetic profiling is related to brain mitochondrial metabolism. While these measures cannot substitute for direct measures of brain metabolism, provided by measures such as FDG-PET, they may have utility as a metabolic biomarker and screening tool to identify individuals exhibiting systemic bioenergetic decline who may therefore be at risk for the development of neurodegenerative diseases.

A NON-HUMAN PRIMATE MODEL OF EARLY ALZHEIMER’S DISEASE PATHOLOGIC CHANGE

various forms and might contain some unstable forms, it is difficult to quantify AbO in degenerative status, such as SDS-PAGE. Therefore, quantitative method of AbO has not been established. Previously, mouse monoclonal anti-AbO form antibody (m6H4) was generated by Matsubara and colleagues (Life Sciences, 2012). In this study, we establish the quantitative measure method of AbO by dot blot assay using m6H4 specific to AbO form in undegenerated status. Methods: Synthetic Ab1–40 monomer and 5-Carboxytetramethylrhodamine (5-TAMRA)-labeled Ab1–40 monomer dissolved in 0.1% ammonium solution (100 mM) were ultra-centrifuged at 540,000 g for 20 h at 4 C to obtain seed-free supernatant. The supernatant fromAb1–40 and 5-TAMRA-labeledAb1–40monomerswere co-incubated to synthesize AbOs at 37 C for 0, 1, 4 and 20 h. Preparing soluble AbOs, the incubated AbO solution were ultra-centrifuged at 100,000 g for 1 h at 4 C. For dot blot assay, 1 mL of soluble AbOs solutions (0, 5, 10, 25 and 50 mM) were spotted on nitrocellulose membrane, and incubated with m6H4 and mouse monoclonal antiAb antibody (4G8) reactive to 17-24 amino acid residue of Ab followed byHRP-labeled secondary antibody and the chemiluminescent substrate. Chemiluminescent signals were visualized using ChemiDoc Touch and quantified using Image Lab software (Bio-Rad Laboratories, Inc.). Results:Signal intensity of AbOs detected by m6H4 demonstrated time-dependent and concentration-dependent upward trends, enabled to make calibration curves which correlation coefficient at each time points were above 0.83 to 0.99. In contrast, signal intensity of Ab monomer and oligomer detected by 4G8 was stable over the period, and detected as concentration-dependent upward trends. The correlation coefficients of calibration curves by 4G8 at each timewere above 0.99. These results suggested that dot blot assay usingm6H4was able to detect AbO specific time dependent and concentration-dependent changes. Conclusions: Production levels of AbOs detected by m6H4 might show time-dependent and concentration-dependent increase. Dot blot assay using our newly developed AbOs specific antibody could be able to quantitate synthetic AbOs.

Automated synthesis of 1-[11C]acetoacetate on a TRASIS AIO module

We automated radiochemical synthesis of 1-[11C]acetoacetate in a commercially available radiochemistry module, TRASIS AllInOne by [11C]carboxylation of the corresponding enolate anion generated in situ from isopropenylacetate and MeLi, and purified by ion-exchange column resins.1-[11C]acetoacetate was synthesized with high radiochemical purity (95%) and specific activity (~ 66.6GBq/µmol, n = 30) with 35% radiochemical yield, decay corrected to end of synthesis. The total synthesis required ~ 16min. PET imaging studies were conducted with 1-[11C]acetoacetate in vervet monkeys to validate the radiochemical synthesis. Tissue uptake distribution was similar to that reported in humans.

DUAL-TRACER ACETOACETATE AND GLUCOSE METABOLISM ARE ASSOCIATED WITH NEUROPATHOLOGIC AMYLOID BURDEN AND ALZHEIMER’S BIOMARKERS IN THE CSF

deposition in PSP (midbrain, caudate, putamen, pallidum, supplementary motor area, superior frontal lobe, pre and post central cortex, and thalamus). Results: The PSP subjects showed evidence for subtle elevated tau-PET uptake compared to CN subjects across all regions. Uptake was particularly evident in midbrain, pallidum, supplementary motor area and precentral cortex (Figure). The degree of tau-PET uptake in PSP was lower than AD across all regions except midbrain, pallidum and thalamus. Subtle regional differences were observed between the different clinical variants of PSP. Uptake was generally the highest in those with Richardson’s syndrome across all regions, except for precentral cortex and supplementary motor area which showed highest uptake in PPAOS. PAGF predominantly involved basal ganglia and post-surgical PSP showed subtle uptake in midbrain and thalamus. Conclusions:PET imaging using AV-1451 can detect a signal across the different clinical variants of PSP, although the degree of uptake is far less than that observed in AD. This ligand may be sensitive enough to detect regional differences across the clinical variants of PSP.

COMBINING STRUCTURAL MRI, PROTEOMIC, AND GENETIC ADNI DATA FOR EARLY DETECTION OF ALZHEIMER'S DISEASE VIA RANDOM FOREST CLASSIFIERS

Data presented as mean (SD) or relative frequencies; HC: Healthy controls; DC: Diseased controls; AD: Dementia due to Alzheimer’s disease; CSF b-amyloid 1-42 values indicative of AD: b-amyloid 1-42 levels in cerebrospinal fluid (CSF) 642 ng/l or 192 pg/ml for themonocentric and multicentric dataset respectively; CSF p-tau values indicative of AD: tau phosphorylated at threonine 181 levels in cerebrospinal fluid (CSF) 61 ng/l or 192 pg/ml for the monocentric and multicentric dataset respectively; CSF t-tau values indicative of AD: total tau levels in cerebrospinal fluid (CSF) 252 ng/l or 94 pg/ml for the monocentric and multicentric dataset respectively. Poster Presentations: P2 P506

RELATIVE IMPACT OF SAMPLE SIZE AND DIMENSIONALITY OF PREDICTORS ON TWO MACHINE LEARNING METHODS FOR DETECTION OF ALZHEIMER'S DISEASE

Background: Spatial gradients in cortical thinning are a hallmark of dementias, and are shown to follow stereotypical patterns specific to each dementia. The signature of the disease is muchmore clearly visible in cortical thickness gradients taken between different brain regions, for example anterior-posterior gradients in AD as AD is known to affect the posterior cortices such as the medial temporal lobes, the precuneus etc. preferentially and early in the course of the disease. Keeping this idea of preferential gradient is mind, We reformulate our previously developed novel imaging cortical biomarker based on graph-theoretic analysis of inter-regional covariance of cortical thickness, called ThickNet features [1] to develop novel covariance features based on dissimilarity in thickness. These features capture the spatial thickness gradients within each subject. We call them Dissimilarity based Extraction of Covariance LInked NEtwork (DECLINE) features.We show that they outperform ThickNet features for the early detection of Alzheimer’s disease. DECLINE features are first of its kind and show promise in detecting the cognitive decline predictive of AD.Methods: Cortical thickness is extracted from the MRI scan using the method [2] for each patient and the features are registered to a common atlas surface to establish vertex-wise correspondence. Then the cortex of each patient is partitioned into large number (e.g. K1⁄4300 vertices per patch) of small areas by k-means clustering of vertices spatially on the atlas surface (Figure 1). A graph is then constructed by establishing a link between two such patches if dissimilarity (abs. difference inmean-thickness) in thickness is above a given threshold (e.g. 0.5mm). From this binary undirected graph, we compute several graph-theoretic properties called DECLINE features to represent each patient (See Figure 2), namely nodal degree, betweenness centrality and clustering coefficient. Using the same ADNI dataset on which we demonstrated the diagnostic utility of ThickNet features, we show that DECLINE features outperform ThickNet features, and show potential for the early detection of Alzheimer’s disease. Results: Using our Repeated Holdout, Stratified Training set (RHsT) cross-validation method proposed in [1] (See Figure 3), DECLINE features produced an area under ROC (AUC) of 0.93 in discriminating AD from healthy controls (CN), and an AUC of 0.87 in discriminating MCI converters (MCIc) from CN. The results presented in Figure 4 show DECLINE features significantly outperform ThickNet features in all the experiments. Conclusions: We present novel DECLINE measures based on inter-regional covariance of cortical thickness from structural MRI and demonstrate their performance on a benchmark ADNI dataset for early detection of Alzheimer’s disease.

MARKERS OF INFLAMMATION AND VASCULAR DYSFUNCTION ARE DIFFERENTIALLY ASSOCIATED WITH HIPPOCAMPAL VOLUME BY COGNITIVE STATUS IN ADNI

Background: Inflammation and vascular dysfunction have been shown to play a role in the pathogenesis of various neurodegenerative diseases, includingAlzheimer’s disease (AD). This study examined the association between total hippocampal volume (HV) and plasma levels of proteins involved in inflammation and vascular injury thatmay contribute tomild cognitive impairment (MCI) and AD. Methods: Alzheimer’s Disease Neuroimaging Initiative-1 (ADNI-1) structural MRI and plasma proteomic data sets were used in this study. Data from 488 ADNI-1 participants were studied, from three diagnostic groups based upon cognitive status: 49 cognitively normal (CN) adults, 330 adults with MCI, and 109 adults with AD. Baseline measurements of HV were determined using FreeSurfer and downloaded from the ADNI website. Multiple linear regressionwas performed to search for associations of 36 plasma proteins involved in inflammation and vascular dysfunction with HV for each of the diagnostic groups, adjusted for age, gender, and BMI. Results: For 10 of the 36 proteins analyzed, higher plasma levels were associated with smaller baseline HV in at least one of the three diagnostic groups. Higher levels of two proteins were significantly associated with smaller HV in more than one group: CD40 antigen (CD40) in MCI (p<0.01) and AD (p<0.05); and Intercellular Adhesion Molecule-1 (ICAM-1) in CN (p<0.05) and MCI (p<0.05). Levels of beta-2-microglobulin (B2M, p<0.005), Vascular Cellular Adhesion Molecule-1 (VCAM-1, p<0.005), Macrophage Inflammatory Protein-1-alpha (MIP-1-alpha, p<0.001), Interleukin-18 (IL-18, p<0.05), and Matrix Metalloproteinase-1/2 (MMP-1/2, p<0.05/p<0.01) were associated with HV in CN, whereas Growth-Regulated alpha protein (GRO-alpha, p<0.05) and Plasminogen Activator Inhibitor-1 (PAI-1, p<0.05) were associated with HV in MCI. Conclusions: Higher plasma levels of 10-of-36 proteins were associated with smaller baseline HVin at least one diagnostic group. These results support previous findings of increased neuroinflammation in MCI and AD, and highlight the potential role of vascular injury. Furthermore, our results may support the importance of inflammatory processes in the early-stage pathogenesis of AD, as 9-of-10 of the associations occurred only in the CN/MCI groups. Validation of these findings with an independent data set is needed to further characterize the association of vascular biomarkers and brain changes associated with MCI/AD.

AN ARTS-BASED BRAIN FITNESS PROGRAM FOR PERSONS WITH DEMENTIA: A PILOT STUDY

Background: Caring for person with dementia often contributes to a high level of caregiver burden. Understanding the major factors contributing to caregiver burden will be useful in designing support programs for caregivers. Methods: A retrospective study of 180 caregivers of dementia from an Asian tertiary institution. The Zarit Burden Interview was administered by trained nurses to evaluate caregiver burden. A higher score indicates higher level of stress and burden. Additional data on demographic factors, socio-economic factors, employment status, age of onset of dementia and severity of the disease were collected. Results: The mean Zarit score for all 180 caregivers was 15.1. 71 caregivers had a Zarit score higher than the mean. Among caregivers with a high burden, 35.19% were caregivers of patients with Young Onset Dementia (YOD) The mean Zarit score of all patients with YOD as 14.1. Caregivers of older patients who were unemployed reported a higher burden score [98.51% vs. 84.96, p 1⁄4 0.007]. The severity of disease also influenced the level of burden. Caregivers of patients who were in the moderate to severe stage of the disease reported significantly higher levels of stress compared to patients in the mild stage of the disease. A higher Zarit score was associated with worse performance on MMSE and [17.61 vs. 20.59, p 1⁄4 0.002] and MOCA [17.11 vs. 19.47, p 1⁄4 0.022] respectively. Age of onset did not influence carergiver’s burden. Conclusions: Severity of dementia and age of dementia onset has a big impact on the caregiver burden. Early education for caregivers on dementia progression and expectations along with timely introduction of coping strategies will be useful in lowering caregiver burden.