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Background Cerebrospinal fluid (CSF) soluble biomarkers are useful at detecting pre‐clinical levels of Alzheimer’s disease (AD) biomarkers of b‐amyloid (Ab) and tau. Disease progression times for participants in longitudinal studies can be estimated for different biomarkers. Utilizing a new technique, this work compared the disease progression times between CSF and PET biomarkers. Methods Four hundred and ten participants from the Alzheimer’s Dementia Onset and Progression in International Cohorts (ADOPIC) including participants form ACS/OASIS, ADNI and AIBL with three or more data points of longitudinal CSF Ab42 and pTau181 (pTau) and Ab PET were selected. PET results were expressed in Centiloid (CL), (299 cognitively unimpaired, 107 mild cognitively impaired, 4 AD dementia; aged 69±9; 216 females (NAIBL=30, NADNI=252, NOASIS=128). Disease trajectory curves for individual biomarkers and the pTau/Ab42 ratio were created by: 1) Fitting a function to the rates of change of the variable of interest versus its mean value), 2) integrating the fit to obtain longitudinal trajectory curves as a function of disease progression time for each of the variables. The participants’ disease progression time along each curve were estimated. Threshold values for Ab PET and pTau/Ab42 ratios were calculated using a gaussian mixture model. Estimates of age of onset were calculated using the progression times. The participants’ disease progression times for each of the different variables were compared using rank correlations. Results Rank correlations for the progression times were: r(Ab42, Ab PET) = 0.75, r(pTau, Ab PET)=0.62, and r(pTau/Ab42, Ab PET)=0.83. The estimated ages at which participants’ reach Ab PET and the pTau/Ab42 ratio thresholds are compared in Fig 1, the average age at which were estimated to reach the threshold values were 55 yr for pTau/Ab42 (threshold of 0.021) and 61 yr for Ab PET (threshold of 22 CL). Conclusions The high correlation between pTau/Ab42 and Ab PET

Background Variability in cognitive decline among adults with Alzheimer’s disease (AD) is seen across studies. While such variability is often modelled using linear models, in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, application of a sigmoidal methodology has shown excellent precision in modelling cognitive and biomarker changes. Here we expand these findings by examining associations of brain volumes in AD specific Regions of Interest (ROIs) with accelerated cognitive decline among amyloid‐beta positive (Ab+) AIBL participants. Method Longitudinal cognitive scores for the AIBL PACC, Language, Visuospatial functioning and CDR‐SB were mapped to sigmoidal trajectories, with a threshold defining the inflection point of accelerated cognitive decline. Participants to the left of the threshold were classified as having non‐accelerated decline (non‐accelerators), and participants beyond the threshold were classed as accelerators (Figure 1B). Using these classifications, we investigated differences in 16 ICV corrected ROI (left and right hemispheres pooled) for reductions in brain volume via generalised linear models adjusted for age, gender, and APOE‐e4 status. Three participant subgroups were tested: 1) Ab+/Tau unknown, 2) Ab+/Tau‐ and 3) Ab+/Tau+. Significant t‐values for the summed ROI volumes were mapped on a standard brain mesh for visualisation. Result Of regions tested, two stood out consistently amongst top markers in each of the participant subgroups and cognitive outcomes: 1) supramarginal volume and 2) middle temporal volume (Figure 1C). Largest volume differences between accelerators and non‐accelerators were seen in the Ab+/Tau+ group; whilst smallest p‐values were in the Ab+/Tau unknown group due to a larger sample size (Table 1). Brain mesh visualization showed most of the AD signature ROIs altered in accelerator groups as compared with non‐accelerator groups. Figure 1D shows the AD signature for each cognitive outcome amongst the Ab+/T

Background Longitudinal tau quantification may provide a useful outcome measure in disease‐specific therapeutic trials. Different tau PET tracers may have different sensitivity to longitudinal changes, but without a head‐to‐head comparison, equating results from different cohorts using different tracers can be biased. In this study, we aim to minimise this bias by matching participants in two cohorts imaged using 18F‐MK6240 and 18F‐Flortaucipir (FTP). Method A subset of 93 participants from AIBL and 93 from ADNI, imaged at baseline and 1 year later using 18F‐MK6240 and 18F‐FTP, respectively, were matched based on baseline clinical diagnosis, MMSE, age, and Centiloid value (CL). PET images were analysed with CapAIBL. Amyloid positivity (+/‐) was defined based on a threshold of 25CL. Subjects were grouped as 34 cognitively unimpaired amyloid negative (CU‐) and 24 positive (CU+), 18 mild cognitive impairment positive (MCI+) and 17 Alzheimer’s disease positive (AD+). Tracer retention was measured in the mesial temporal (Me), meta‐temporal (MT), temporoparietal (Te) and rest of the cortex (R). T‐tests were employed to assess group separation at baseline using SUVR and longitudinally using SUVR/Yr. Result As per selection criteria, there were no significant differences in age, MMSE or Centiloid between the cohorts using 18F‐MK6240 or 18F‐FTP in each subgroups. Baseline SUVR were significantly different between CU‐/CU+, CU+/MCI+ and CU+/AD+ in all regions for both tracers, except for CU‐/CU+ in R for 18F‐MK6240 (Figure 1). Using 18F‐MK6240, rate of change in CU+ was significantly higher than CU‐ in MT and Te, and both MCI+ and AD+ were higher than CU+ in R (Figure 2.Left). Using 18F‐FTP, rate of change in MCI+ was significantly higher than CU+ in Te, and AD+ higher than CU+ in MT, Te and R (Figure 2.Right). Conclusion In our matched cohorts using 18F‐MK6240 or 18F‐FTP, we found that, at baseline, both tracers can detect significant differences between clinical groups. Howe

In this article the affiliation details for Ulman Lindenberger were incorrectly given as ‘Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany’ but should have been ‘Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany’, ‘Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany’. The original article has been corrected.

PURPOSE: Cancer-related cognitive impairment (CRCI) is a recognised adverse consequence of cancer and its treatment. This study assessed the feasibility of collecting longitudinal data on cognition in patients with newly diagnosed, aggressive lymphoma undergoing standard therapy with curative intent via self-report, neuropsychological assessment, peripheral markers of inflammation, and neuroimaging. An exploration and description of patterns of cancer-related cognitive impairment over the course of treatment and recovery was also undertaken and will be reported separately. METHODS: Eligible participants completed repeated measures of cognition including self-report and neuropsychological assessment, and correlates of cognition including blood cell-based inflammatory markers, and neuroimaging at three pre-specified timepoints, time 1 (T1) - pre-treatment (treatment naïve), time 2 (T2) - mid-treatment, and time 3 (T3) - 6 to 8 weeks post-completion of treatment. RESULTS: 30/33 eligible patients (91%, 95% CI: 76%, 97%) were recruited over 10 months. The recruitment rate was 3 patients/month (95% CI: 2.0, 4.3 patients/month). Reasons for declining included feeling overwhelmed and rapid treatment commencement. Mean age was 57 years (SD = 17 years) and 16/30 (53%) were male. Most patients (20/30, 67%) had diffuse large B cell lymphoma or Hodgkin lymphoma (4/30, 13%). The neuroimaging sub-study was optional, 11/30 participants (37%) were eligible to take part, and all agreed. The remaining 19 participants were ineligible as their diagnostic PET/CT scan was completed prior. Retention and compliance with all assessments were 89 to 100% at all timepoints. Only one participant was withdrawn due to disease progression. CONCLUSIONS: Findings from this study including excellent recruitment, retention, and compliance rates demonstrate it is feasible to longitudinally assess cognition in people with newly diagnosed aggressive lymphoma during their initial treatment and recovery to

Background Previous studies have shown that Aß‐amyloid (Aß) likely promotes tau to spread beyond the medial temporal lobe. However, the Aß levels necessary for tau to spread in the neocortex is still unclear. Method 466 participants underwent tau imaging with [18F]MK6420 and Aß imaging with [18F]NAV4694 (Fig. 1). Aß scans were quantified on the Centiloid (CL) scale with a cut‐off of 25CL for abnormal levels of Aß (A+). Tau scans were quantified in three regions of interest (ROI) (mesial temporal (Me); temporoparietal neocortex (Te); and rest of neocortex (R)) and four mesial temporal region (entorhinal cortex, amygdala, hippocampus and parahippocampus) using the cerebellar cortex as reference region. Regional tau thresholds were established as the 95%ile of the cognitively unimpaired A‐ subjects. The prevalence of abnormal tau levels (T+) along the Centiloid continuum was determined. Result The plots of prevalence of T+ (Fig. 2) show earlier and greater increase along the Centiloid continuum in the medial temporal area compared to neocortex. Prevalence of T+ was low but associated with Aß level between 10‐40 CL reaching 23% in Me, 15% in Te and 11% in R. Between 40‐70 CL, the prevalence of T+ subjects per CL increased four‐fold faster and at 70 CL was 64% in Me, 51% in Te and 37% in R. In cognitively unimpaired (Fig. 3), there were no T+ in R below 50 CL. The highest prevalence of T+ was found in the entorhinal cortex, reaching 40% at 40 CL and 80% at 60 CL. Conclusion Outside the entorhinal cortex, abnormal levels of cortical tau on PET are rarely found with Aß levels below 40 CL. Above 40 CL prevalence of T+ accelerates in all areas. Moderate Aß levels are required before neocortical tau becomes detectable.

Background The introduction of the AT(N) framework raised several issues in regards to the definition of T+. What brain regions should be sampled? Based on one or on multiple tracers? In this work, we developed a “universal” cortical tau mask for the AD continuum derived from all the major tau ligands. This “universal” cortical mask will serve as the common tau area for all tracers over which several different regional sampling VOI or composites can be then applied. Guaranteeing sampling of the same common regions is the first step to develop a common scale for all tau tracers: the CenTauR. Method 464 participants underwent tau scans with either 18F‐AV1451 (CN=54/AD=24), 18F‐MK6240 (CN=157/AD=22), 18F‐PI2620 (CN=10/AD=21), 18F‐PM‐PBB3 (CN=30/AD=28), 18F‐GTP1 (CN=15/AD=38) or 18F‐RO948 (CN=35/AD=30). All CN were Aß‐ and all AD were Aß+. The tau scans were spatially normalized using CapAIBL and the cerebellar cortex was used as reference region. For each tracer, a difference image between the means of the Aß‐ CN and Aß+ AD patients was generated. Difference images were subsequently thresholded at 1/3 of the difference between Aß‐ CN and Aß+ AD in the inferior temporal lobe. A single tau specific mask was then constructed from the intersection of all the specific tau tracer masks. A MRI‐derived grey matter mask at PET resolution was applied to the composite mask only sampling grey matter regions. Finally, the mask was mirrored and fused to remove the hemispherical asymmetry of tau pathology. Agreement between masks was assessed by dice‐scores. Result Visually, all the tracer‐specific masks appeared very similar. None of the known off‐target binding regions were discernible in the resulting masks (Figure 1). There was good agreement between all masks, with dice‐scores of 0.60 and 0.66 for cortical regions. Conclusion We constructed an “universal” tau mask for the AD continuum based on all the commonly used tau tracers aiming at standardizing tau sampling and quantificat

BACKGROUND: [18F]flutemetamol PET scanning provides information on brain amyloid load and has been approved for routine clinical use based upon visual interpretation as either negative (equating to none or sparse amyloid plaques) or amyloid positive (equating to moderate or frequent plaques). Quantitation is however fundamental to the practice of nuclear medicine and hence can be used to supplement amyloid reading methodology especially in unclear cases. METHODS: A total of 2770 [18F]flutemetamol images were collected from 3 clinical studies and 6 research cohorts with available visual reading of [18F]flutemetamol and quantitative analysis of images. These were assessed further to examine both the discordance and concordance between visual and quantitative imaging primarily using thresholds robustly established using pathology as the standard of truth. Scans covered a wide range of cases (i.e. from cognitively unimpaired subjects to patients attending the memory clinics). Methods of quantifying amyloid ranged from using CE/510K cleared marked software (e.g. CortexID, Brass), to other research-based methods (e.g. PMOD, CapAIBL). Additionally, the clinical follow-up of two types of discordance between visual and quantitation (V+Q- and V-Q+) was examined with competing risk regression analysis to assess possible differences in prediction for progression to Alzheimer's disease (AD) and other diagnoses (OD). RESULTS: Weighted mean concordance between visual and quantitation using the autopsy-derived threshold was 94% using pons as the reference region. Concordance from a sensitivity analysis which assessed the maximum agreement for each cohort using a range of cut-off values was also estimated at approximately 96% (weighted mean). Agreement was generally higher in clinical cases compared to research cases. V-Q+ discordant cases were 11% more likely to progress to AD than V+Q- for the SUVr with pons as reference region. CONCLUSIONS: Quantitation of amyloid PET shows a hig

Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.

INTRODUCTION: Cancer-related cognitive impairment (CRCI) is a distressing and disabling side-effect of cancer treatments affecting up to 75% of patients. For some patients, their cognitive impairment may be transient, but for a subgroup, these symptoms can be long-standing and have a major impact on the quality of life. This paper describes the protocol for a study: (1) to assess the feasibility of collecting longitudinal data on cognition via self-report, neuropsychological testing, peripheral markers of inflammation and neuroimaging and (2) to explore and describe patterns of cancer-related cognitive impairment over the course of treatment and recovery in patients with newly diagnosed, aggressive lymphoma undergoing standard therapy with curative intent. METHODS AND ANALYSIS: This is a prospective, longitudinal, feasibility study in which 30 newly diagnosed, treatment-naive patients with aggressive lymphoma will be recruited over a 12-month period. Patients will complete comprehensive assessments at three time points: baseline (time 1, pre-treatment) and two post-baseline follow-up assessments (time 2, mid-treatment and time 3, 6-8 weeks post-treatment completion). All patients will be assessed for self-reported cognitive difficulties and objective cognitive function using Stroop Colour and Word, Trail Making Test Part A and B, Hopkins Verbal Learning Test-Revised, Controlled Oral Word Association and Digit Span. Blood cell-based inflammatory markers and neuroimaging including a positron emission tomography (PET) with 18F-labelled fluoro-2-deoxyglucose (18F-FDG) and CT (18F-FDG-PET/CT) and a MRI will explore potential inflammatory and neuroanatomical or functional mechanisms and biomarkers related to CRCI. The primary intent of analysis will be to assess the feasibility of collecting longitudinal data on cognition using subjective reports and objective tasks from patients during treatment and recovery for lymphoma. These data will inform the design of a larger-sca

Motor deficits in parkinsonism are caused by degeneration of dopaminergic nigral neurons. The success of disease-modifying therapies relies on early detection of the underlying pathological process, leading to early interventions in the disease phenotype. Healthy (n = 16), REM sleep behavior disorder (RBD) (n = 14), dementia with Lewy bodies (n = 10), and Parkinson's disease (PD) (n = 20) participants underwent 18F-AV133 vesicular monoamine transporter type-2 (VMAT2) PET to determine the integrity of the nigrostriatal pathway. Clinical, neurophysiological and neuropsychological testing was conducted to assess parkinsonian symptoms. There was reduced VMAT2 levels in RBD participants in the caudate and putamen, indicating nigrostriatal degeneration. RBD patients also presented with hyposmia and anxiety, non-motor symptoms associated with parkinsonism. 18F-AV133 VMAT2 PET allows identification of underlying nigrostriatal degeneration in RBD patients. These findings align with observations of concurrent non-motor symptoms in PD and RBD participants of the Parkinson's Progression Markers Initiative. Together, these findings suggest that RBD subjects have prodromal parkinsonism supporting the concept of conducting neuroprotective therapeutic trials in RBD-enriched cohorts. Ongoing longitudinal follow-up of these subjects will allow us to determine the time-window of clinical progression.

Numerous animal studies have reported exercise reduces the accumulation of Alzheimer’s disease pathology, including amyloid-β (Aβ) and tau. Furthermore, we previously reported a relationship between higher levels of physical activity (PA) and lower brain Aβ burden in a human population. The recent advent of tau positron emission tomography (PET) tracers enables us to extend our investigations into the evaluation of the relationship between PA and brain tau burden. Utilizing data from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, we have examined the cross-sectional relationship between habitual PA and PET-quantified tau burden. Forty-three cognitively healthy older adults were categorized into low-moderate PA (LMPA; n = 16) or high PA (HPA; n = 27), based on self-reported PA levels. Tau PET imaging with the AV1451 tracer was conducted on all participants. The LMPA group had significantly higher neocortical tau burden (presented as a z-score; 1.22±1.98), compared to the HPA group (z-score: – 0.28±1.18). The difference between the LMPA and HPA groups was also evident when examining regional tau burden in the temporoparietal cortex and the prefrontal cortex. Our results suggest an association between self-reported PA level and brain tau burden. Future longitudinal and interventional studies utilizing larger samples sizes are vital to further investigate the nature of the relationship between tau and PA.

OBJECTIVES: To further validate the diagnostic utility of 18F-AV-133 vesicular monoamine transporter type 2 (VMAT2) positron emission tomography (PET) in patients with clinically uncertain parkinsonian syndromes (CUPS) by comparison to clinical diagnosis at 3 years follow-up. DESIGN, SETTING AND PARTICIPANTS: In a previous study, we reported that 18F-AV-133 PET in community patients with CUPS changed diagnosis and management and increased diagnostic confidence. The current diagnosis of this cohort was obtained from the patient and treating specialist and compared with the diagnosis suggested 3 years earlier by the 18F-AV-133 PET. A second 18F-AV-133 PET was available in those with a discordant or inconclusive final diagnosis. STUDY OUTCOME MEASURES: The primary end point was the proportion of patients who had a follow-up clinical diagnosis, which was concordant with their initial 18F-AV-133 PET scan. Secondary end points were the proportion of patients who had the same diagnosis at follow-up as that reached after the initial scan and the stability of diagnostic changes made after the first scan. RESULTS: 81 of the 85 patients previously recruited to the CUPS study had follow-up of which 79 had a clinical diagnosis and 2 remained CUPS. The diagnosis was in agreement with the initial 18F-AV-133 PET scan result in 74 cases. Five patients had a discordant diagnosis; one patient with rubral tremor had a severely abnormal scan that had worsened when rescanned; four cases with normal initial and repeat scans had a clinical diagnosis of Parkinson's disease. Two patients with suspected genetic disorders remained classified as CUPS and both had normal scans. In the 24 CUPS cohort patients where 18F-AV-133 PET initially changed diagnosis, this change was supported by follow-up diagnosis in all but the one rubral tremor case. CONCLUSION: 18F-AV-133 PET is a useful tool in improving diagnostic accuracy in CUPS providing results and diagnostic changes that remain robust after 3 y

Alzheimer's Disease (AD) is the most common form of dementia, characterised by extracellular amyloid deposition as plaques and intracellular neurofibrillary tangles of tau protein. As no current clinical test can diagnose individuals at risk of developing AD, the aim of this project is to evaluate a blood-based biomarker panel to identify individuals who carry this risk. We analysed the levels of 22 biomarkers in clinically classified healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer's participants from the well characterised Australian Imaging, Biomarker and Lifestyle (AIBL) study of aging. High levels of IL-10 and IL-12/23p40 were significantly associated with amyloid deposition in HC, suggesting that these two biomarkers might be used to detect at risk individuals. Additionally, other biomarkers (Eotaxin-3, Leptin, PYY) exhibited altered levels in AD participants possessing the APOE ϵ4 allele. This suggests that the physiology of some potential biomarkers may be altered in AD due to the APOE ϵ4 allele, a major risk factor for AD. Taken together, these data highlight several potential biomarkers that can be used in a blood-based panel to allow earlier identification of individuals at risk of developing AD and/or early stage AD for which current therapies may be more beneficial.

Background Brain amyloid β (Aβ) deposition and neurodegeneration have been documented in about 50–60% of cognitively healthy elderly individuals (aged 60 years or older). The long-term cognitive consequences of the presence of Alzheimer's disease pathology and neurodegeneration, and whether they have an independent or synergistic effect on cognition, are unclear. We aimed to characterise the long-term clinical and cognitive trajectories of healthy elderly individuals using a two-marker (Alzheimer's disease pathology and neurodegeneration) imaging construct. Methods Between Nov 3, 2006, and Nov 25, 2014, 573 cognitively healthy individuals in Melbourne and Perth, Australia, (mean age 73·1 years [SD 6·2]; 58% women) were enrolled in the Australian Imaging, Biomarker and Lifestyle (AIBL) study. Alzheimer's disease pathology (A) was determined by measuring Aβ deposition by PET, and neurodegeneration (N) was established by measuring hippocampal volume using MRI. Individuals were categorised as A−N−, A+N−, A+N+, or suspected non-Alzheimer's disease pathophysiology (A−N+, SNAP). Clinical progression, hippocampal volume, standard neuropsychological tests, and domain-specific and global cognitive composite scores were assessed over 6 years of follow-up. Linear mixed effect models and a Cox proportional hazards model of survival were used to evaluate, compare, and contrast the clinical, cognitive, and volumetric trajectories of patients in the four AN categories. Findings 50 (9%) healthy individuals were classified as A+N+, 87 (15%) as A+N−, 310 (54%) as A−N−, and 126 (22%) as SNAP. APOE ε4 was more frequent in participants in the A+N+ (27; 54%) and A+N− (42; 48%) groups than in the A−N− (66; 21%) and SNAP groups (23; 18%). The A+N− and A+N+ groups had significantly faster cognitive decline than the A−N− group (0·08 SD per year for AIBL-Preclinical AD Cognitive Composite [PACC]; p<0·0001; and 0·25; p<0·0001; respectively). The A +N+ group also had faster hippocampal atrophy t

Alzheimer’s disease (AD) is a degenerative brain disorder and is the most common form of dementia. Minimally invasive approaches are required that combine biomarkers to identify individuals who are at risk of developing mild cognitive impairment (MCI) and AD, to appropriately target clinical trials for therapeutic discovery as well as lifestyle strategies aimed at prevention. Buccal mucosa cells from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing cohort (n=60) were investigated for cytological markers that could be used to identify both MCI and AD individuals. Visual scoring of the buccal cytome demonstrated a significantly lower frequency of basal and karyorrhectic cells in the MCI group compared with controls. A high content, automated assay was developed using laser scanning cytometry to simultaneously measure cell types, nuclear DNA content and aneuploidy, neutral lipid content, putative Tau and amyloid-β (Aβ) in buccal cells. DNA content, aneuploidy, neutral lipids and Tau were similar in all groups. However, there was significantly lower Tau protein in both basal and karyolytic buccal cell types compared with differentiated buccal cells. Aβ, as measured by frequency of cells containing Aβ signal, as well as area and integral of Aβ signal, was significantly higher in the AD group compared with the control group. Buccal cell Aβ was correlated with mini-mental state examination (MMSE) scores (r = -0.436, P=0.001) and several blood-based biomarkers. Combining newly identified biomarkers from buccal cells with those already established may offer a potential route for more specific biomarker panels which may substantially increase the likelihood of better predictive markers for earlier diagnosis of AD.

© 2016 American Association for Geriatric PsychiatryObjective To examine how ß-amyloid (Aß), APOE and BDNF genotypes, and cortisol relate to depressive and anxiety symptoms in cognitively normal older women and men. Methods Cross-sectional data were analyzed from 423 older adults from the Australian Imaging Biomarkers and Lifestyle study. Analyses of covariance evaluated associations between Aß, APOE and BDNF genotype, and cortisol in relation to severity of depressive and anxiety symptoms. Results Among Aß+ older adults, APOE e4 carriage was associated with greater severity of anxiety symptoms (d?=?0.55); and in the full sample, APOE e4 carriage was linked to greater severity of depressive (d?=?0.26) and anxiety (d?=?0.21) symptoms. Among Aß+ women, e4 carriers reported greater anxiety symptoms than non-e4 carriers (d?=?0.83), and female BDNF rs6265 Val66 Met allele carriers reported greater depressive symptoms (d?=?0.29). Conclusion Sex moderated the relationship between Aß, APOE genotype, and BDNF genotype in predicting severity of anxiety and depressive symptoms in cognitively normal older adults.

11C-Pittsburgh compound B (PiB) is a positron emission tomography (PET) tracer designed to bind to amyloid-β (Aβ) plaques, one of the hallmarks of Alzheimer's disease (AD). The potential of PiB as an early marker of AD led to the increasing use of PiB in clinical research studies and development of several F-18–labeled Aβ radiotracers. Automatic quantification of PiB images requires an accurate parcellation of the brain's gray matter (GM). Typically, this relies on a coregistered magnetic resonance imaging (MRI) to extract the cerebellar GM, compute the standardized uptake value ratio (SUVR), and provide parcellation and segmentation for quantification of regional and global SUVR. However, not all subjects can undergo MRI, in which case, an MR-less method is desirable. In this study, we assess 3 PET-only quantification methods: a mean atlas, an adaptive atlas, and a multi-atlas approaches on a database of 237 subjects having been imaged with both PiB PET and MRI. The PET-only methods were compared against MR-based SUVR quantification and evaluated in terms of correlation, average error, and performance in classifying subjects with low and high Aβ deposition. The mean atlas method suffered from a significant bias between the estimated neocortical SUVR and the PiB status, resulting in an overall error of 5.6% (R2 = 0.98), compared with the adaptive and multi-atlas approaches that had errors of 3.06% and 2.74%, respectively (R2 = 0.98), and no significant bias. In classifying PiB-negative from PiB-positive subjects, the mean atlas had 10 misclassified subjects compared with 0 for the adaptive and 1 for the multi-atlas approach. Overall, the adaptive and the multi-atlas approaches performed similarly well against the MR-based quantification and would be a suitable replacements for PiB quantification when no MRI is available.

Pittsburgh Compound B (PiB) is a C11 PET tracer designed to bind to amyloid plaques, one of the hallmark of Alzheimer's disease. The potential of PiB as an early marker of Alzheimer's disease has lead to an increasing use of PiB and the development of several F18 equivalents. Quantitative analysis of PiB images requires an accurate normalisation, parcellation and estimation of retention in the brain's gray matter. Typically this relies on co-registered MRI to extract the cerebellum, compute the standardized uptake value ratio (SUVR) and provide parcellation and segmentation for quantification of neocortical SUVR. However, not all subjects undergo MRI. In this paper we propose a highly accurate MR-less parcellation, SUVR normalisation and quantification method for PiB images. This involves rigidly registering the raw PiB images to a PiB atlas, computing pair-wise normalised mutual information, and constructing a 2D manifold. Each new scan is mapped on the manifold and its k nearest neighbours are selected as atlases in a segmentation propagation scheme with their associated MRI segmentations and parcellation used as priors to estimate the SUVR normalisation and quantification. Comparison of our MRless approach to an MR-based approach showed a coefficient of correlation of neocortical PiB SUVR of R2=0.94 and an absolute mean error of 5.9%.