William R. Shankle

Early clinical PET imaging results with the novel PHF-tau radioligand [F18]-T808.

Aggregates of hyperphosphorylated tau (PHF-tau), such as neurofibrillary tangles, are linked to the degree of cognitive impairment in Alzheimers disease. We have recently reported early clinical results of a novel PHF-tau targeting PET imaging agent, [F18]-T807. Since then, we have investigated a second novel PHF-tau targeting PET imaging agent, [F18]-T808, with different pharmacokinetic characteristics, which may be favorable for imaging Alzheimers disease and other tauopathies. Here, we describe the first human brain images with [F18]-T808.

A new EEG method for estimating cortical neuronal impairment that is sensitive to early stage Alzheimer's disease

OBJECTIVES To test the hypothesis that elecetroencephalographic (EEG) analysis is sensitive to cortical neuronal impairment in early stage Alzheimers disease (AD), and that this analysis correlates with corresponding changes in cerebral blood flow. METHODS We examined an EEG measure of neuronal impairment in the cerebral cortex in terms of its ability to detect very mild AD. This measure, the mean value of the resting state EEG alpha dipolarity (D(alpha)), approaches unity without cortical sulcal lesions, whereas brains with randomly distributed cortical sulcal lesions lower D(alpha) values well below unity. D(alpha) was evaluated in 25 patients with very mild AD, 33 patients with moderately severe AD, and 56 normal age-matched subjects. These subjects also received SPECT, and strong correlation between D(alpha) and regional cerebral blood flow (rCBF) was observed. RESULTS D(alpha) values greater than 0.977 correctly classified normal subjects, but also included 10% of very mild AD. D(alpha) values less than 0.952 correctly classified very mild AD as well as moderately severe AD, but also included 10% of normal subjects. D(alpha) values also correlated positively with bilateral temporal-parietal rCBF (a characteristic finding in AD patients); both declined with increasing dementia severity. CONCLUSIONS Analysis of D(alpha) in this sample supports the hypothesis that early stages of AD can be discriminated from normal aging using measures of cortical neuronal impairment. Furthermore, dementia severity, as reflected by the degree of impairment, is reflected in declining D(alpha) values and increasing variance (greater spread of the D(alpha) values).

Approximate doubling of numbers of neurons in postnatal human cerebral cortex and in 35 specific cytoarchitectural areas from birth to 72 months.

ABSTRACT From 1939 to 1967, J.L. Conel quantitatively studied the microscopic features of the developing human cerebral cortex and published the findings in eight volumes. We have constructed a database using his neuroanatomical measurements (neuronal packing density, myelinated large fiber density, large proximal dendrite density, somal breadth and height, and total cortical and cortical layer thickness) at the eight age periods (0 [term birth], 1, 3, 6, 15, 24, 48, and 72 postnatal months) he studied. In this report, we examine changes in neuron numbers over the eight age-points for 35 von Economo areas for which Conel gave appropriate data. From birth to 3 months postnatal age, total cortical neuron number increases 23–30%, then falls to within 3.5% of the birth value at 24 months, supporting our previous work showing that the observed decrease in the number of neurons per column of cortex under a 1-mm2 cortical surface from birth to 15 months is almost entirely due to cortical surface expansion. The present study also shows a 60–78% increase in total cortical neuron number above the birth value from postnatal ages 24 to 72 months. The generalization, to humans at least, of the finding of no postnatal neurogenesis in rhesus macaques, a species belonging to a superfamily that diverged from that of Homo sapiens more than 25 million years ago, is not warranted until explicitly proven for humans. The data of the present study support the existence of substantial postnatal neurogenesis in humans for the 35 cortical areas studied.

Should older adults be screened for dementia

The question of whether to screen for dementia and Alzheimers disease (AD) has been discussed in many forums throughout the world. Generally, medical advisory groups and policy‐making groups have recognized the importance of early diagnosis but have uniformly avoided making recommendations to screen at‐risk populations. This presentation reflects the support for reconsidering the importance of screening individuals at risk or above a certain age. In this statement, the majority of the authors support the consideration of dementia risk factors in individuals at age 50, with routine yearly screening after 75. Other authors remain concerned that the benefits of treatments of early disease do not yet support a general screening recommendation. These statements are made to encourage progress toward the development of a consensus regarding the widespread institution of screening policy. Accordingly, members of the worldwide scientific community are invited to add their perspective by contributing short commentaries (1500 words) on this subject.

Should older adults be screened for dementia? It is important to screen for evidence of dementia!

Multiple arguments for considering routine dementia screening have been presented. Furthermore, dementia diagnoses are widely unrecognized. As a result, persons with dementia are missing important clinical care and treatment interventions. By distinction, the problems of defining, diagnosing, and treating mild cognitive impairment (MCI) are not yet resolved, and MCI is not ready for a screening recommendation. Dementia screening approaches, including cognitive testing and functional assessment, must be evaluated on their scientific merits, including sensitivity and specificity for recognizing affected individuals in at‐risk populations. Screening tests must be “cost‐worthy”, with the benefits of true‐positive test results justifying the costs of testing and resolving false‐positive cases, with due consideration for proper diagnostic evaluation and potential harms. With the tremendous number of new cases projected in the near future and the expected emergence of beneficial therapies, considerably more research is needed to develop more efficient screening systems.

Capillary electrophoresis‐mass spectrometry‐based metabolome analysis of serum and saliva from neurodegenerative dementia patients

Despite increasing global prevalence, the precise pathogenesis and terms for objective diagnosis of neurodegenerative dementias remain controversial, and comprehensive understanding of the disease remains lacking. Here, we conducted metabolomic analysis of serum and saliva obtained from patients with neurodegenerative dementias (n = 10), including Alzheimers disease, frontotemporal lobe dementia, and Lewy body disease, as well as from age‐matched healthy controls (n = 9). Using CE‐TOF‐MS, six metabolites in serum (β‐alanine, creatinine, hydroxyproline, glutamine, iso‐citrate, and cytidine) and two in saliva (arginine and tyrosine) were significantly different between dementias and controls. Using multivariate analysis, serum was confirmed as a more efficient biological fluid for diagnosis compared to saliva; additionally, 45 metabolites in total were identified as candidate markers that could discriminate at least one pair of diagnostic groups from the healthy control group. These metabolites possibly provide an objective method for diagnosing dementia‐type by multiphase screening. Moreover, diagnostic‐type‐dependent differences were observed in several tricarboxylic acid cycle compounds detected in serum, indicating that some pathways in glucose metabolism may be altered in dementia patients. This pilot study revealed novel alterations in metabolomic profiles between various neurodegenerative dementias, which would contribute to etiological investigations.

Kinetics of the Tau PET Tracer 18F-AV-1451 (T807) in Subjects with Normal Cognitive Function, Mild Cognitive Impairment, and Alzheimer Disease.

We report kinetic modeling results of dynamic acquisition data from 0 to 100 min after injection with the tau PET tracer 18F-AV-1451 in 19 subjects. Methods: Subjects were clinically diagnosed as 4 young cognitively normal, 5 old cognitively normal, 5 mild cognitive impairment, and 5 Alzheimer disease (AD). Kinetic modeling was performed using Logan graphical analysis with the cerebellum crus as a reference region. Voxelwise binding potential (BP) and SUV ratio (SUVR80−100) images were compared. Results: In AD subjects, slower and spatially nonuniform clearance from cortical regions was observed as compared with the controls, which led to focal uptake and elevated retention in the imaging data from 80 to 100 min after injection. BP from the dynamic data from 0 to 100 min correlated strongly (R2 > 0.86) with corresponding regional SUVR80−100−1 values. In the putamen, the observed kinetics (positive SUVR1−5−1 at the tracer delivery stage and plateauing time–SUVR curves for all diagnostic categories) may suggest either additional off-target binding or a second binding site with different kinetics. Conclusion: The kinetics of the 18F-AV-1451 tracer in cortical areas, as examined in this small group of subjects, differed by diagnostic stage. A delayed 80- to 100-min scan provided a reasonable substitute for a dynamic 0- to 100-min acquisition for cortical regions although other windows (e.g., 75–105 min) may be useful to evaluate.

THE DEVELOPMENT OF STRUCTURE AND FUNCTION IN THE POSTNATAL HUMAN CEREBRAL CORTEX FROM BIRTH TO 72 MONTHS: CHANGES IN THICKNESS OF LAYERS II AND III CO-RELATE TO THE ONSET OF NEW AGE-SPECIFIC BEHAVIORS

HYPOTHESIS The thickness of a cortical layer is a composite measure of neuronal, axonal, dendritic, synaptic, and glial numbers and sizes that may relate to thefunction of a cortical area. METHODS 35 age-specific behaviors with defined cortical localization whose onset lies between birth and 72 months were selected. Each behaviors function localized to one or more of 12 cytoarchitectonic areas (Brodmann areas 4, with homuncular subdivisions for leg, trunk, face, and hand, plus 17, 18, 19, 20, 21, 24, 36, and 37). Data on cortical thickness for each layer of 41 cytoarchitectonic areas (including the 12 above) of the postnatal human cerebral cortex from birth of 72 months were analyzed for general patterns of change. For the 12 cortical areas functionally related to theage-specific behaviors, we searched for layer thickness changes that co-related to when the behaviors began. RESULTS Without exception, all layers of the 41 cortical areas of the postnatal human cerebral cortex studied develop through a series of repeated thinning and thickening in a wave-like fashion. With regard to the co-relation of behavioral onset and changes in cortical layer thickness, from birth to 15 months, only layer II has agreater than expected frequency of being the layer with the greatest relative change in thickness (relative to its previous value). From 15 to 72 months, only layer IlI has a greater than expected frequency of being the layer with the greatest absolute change in thickness (81% involved a change in its direction of growth (thinning <--> thickening)). The co-occurrence of directional growth change and having the greatest layer thickness change were only statistically significant for layer III when an age-specific behavior began and was not seen for the 41 cortical areas overall (p = 0.014). CONCLUSIONS Cortical laminar development exhibits aprocess that is mathematically consistent with a random walk with drift and with boundaries so that uncontrolled proliferation and pruning are prevented. The directional changes in layer growth could be controlled by feedback coupled with growth promoting and growth inhibiting factors. Layer II, with its function of establishing local corticocortical connections, appears to be most important in establishing age-specific behaviors of infants from birth to 15 months. Such a process tends to produce relatively simpler behaviors. LayerIII, with its function of establishing longer distance corticocortical connections, appears to be most important in establishing age-specific behaviors of children from 15 to 72 months. This process tends to produce richer, more cross-modal behaviors than those mediated primarily by local corticocortical interactions.

Approximating dipoles from human EEG activity: the effect of dipole source configuration on dipolarity using single dipole models

Dipolarity is the goodness-of-fit of the observed potential distribution with one calculated using specific assumptions about the source of the electrical potential distribution. The authors used computer simulations to examine the effect of different distributions of sources on their resulting dipolarity values. Electric dipoles were placed in a head-shaped model with uniform conductivity using four different dipole configurations (randomly oriented dipoles, a uniform dipole disk layer, a dipole disk layer with uniformly distributed holes, or one with randomly oriented dipoles). The best-fitting single dipole for each configuration was calculated and the dipolarity was computed as the mean squared error of the electrical potential distributions generated by the actual dipole configuration and by the best-fitting single dipole. The simulations show that: 1) a smooth dipole layer with or without holes gives dipolarities above 99.5% even when extended over areas as large as 1256 mm/sup 2/; 2) randomly oriented dipoles under a smooth dipole layer also give dipolarities above 99.5%; and 3) randomly oriented and distributed dipoles, even if contained in a small portion of the total area, give dipolarities below 93.0%. These simulations show that inhomogeneity (holes) within a dipole disk layer per se do not lower dipolarity; rather, it is the random orientation and distribution of these dipoles which lowers dipolarity. Furthermore, dipolarity is not lowered by such randomly oriented and distributed dipoles when they are beneath a dipole disk layer.

Two-Stage Machine Learning model for guideline development

We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clinical settings is at present complex and highly subjective because of the ambiguities and the complicated nature of existing guidelines. Our model abstracts the two-stage process used by physicians to arrive at the global Clinical Dementia Rating Scale (CDRS) score. The model incorporates learning intermediate concepts (CDRS category scores) in the first stage that then become the feature space for the second stage (global CDRS score). The sample consisted of 678 patients evaluated in the Alzheimers Disease Research Center at the University of California, Irvine. The demographic variables, functional and cognitive test results used by physicians for the task of dementia severity staging were used as input to the machine learning algorithms. Decision tree learners and rule inducers (C4.5, Cart, C4.5 rules) were selected for our study as they give expressive models, and Naive Bayes was used as a baseline algorithm for comparison purposes. We first learned the six CDRS category scores (memory, orientation, judgement and problem solving, personal care, home and hobbies, and community affairs). These learned CDRS category scores were then used to learn the global CDRS scores. The Two-Stage ML model classified as well as or better than the published inter-rater agreements for both the category and global CDRS scoring by dementia experts. Furthermore, for the most critical distinction, normal versus very mildly impaired, the Two-Stage ML model was 28.1 and 6.6% more accurate than published performances by domain experts. Our study of the CDRS examined one of the largest, most diverse samples in the literature, suggesting that our findings are robust. The Two-Stage ML model also identified a CDRS category, Judgment and Problem Solving, which has low classification accuracy similar to published reports. Since this CDRS category appears to be mainly responsible for misclassification of the global CDRS score when it occurs, further attribute and algorithm research on the Judgment and Problem Solving CDRS score could improve its accuracy as well as that of the global CDRS score.