Cerebral microbleeds (microbleeds) are small, punctuate hypointense lesions seen in T2* Gradient-Recall Echo (GRE) and Susceptibility-Weighted (SWI) Magnetic Resonance Imaging (MRI) sequences, corresponding to areas of hemosiderin breakdown products from prior microscopic hemorrhages. They occur in the setting of impaired small vessel integrity, commonly due to either hypertensive vasculopathy or cerebral amyloid angiopathy. Microbleeds are more prevalent in individuals with Alzheimer’s disease (AD) dementia and in those with both ischemic and hemorrhagic stroke. However they are also found in asymptomatic individuals, with increasing prevalence with age, particularly in carriers of the Apolipoprotein (APOE) ε4 allele. Other neuroimaging findings that have been linked with microbleeds include lacunar infarcts and white matter hyperintensities on MRI, and increased cerebral β-amyloid burden using 11C-PiB Positron Emission Tomography. The presence of microbleeds has been suggested to confer increased risk of incident intracerebral hemorrhage – particularly in the setting of anticoagulation – and of complications of immunotherapy for AD. Prospective data regarding the natural history and sequelae of microbleeds are currently limited, however there is a growing evidence base that will serve to inform clinical decision-making in the future.

Non-invasive imaging of tau pathology in the living brain would be useful for accurately diagnosing Alzheimer's disease, tracking disease progression, and evaluating the treatment efficacy of disease-specific therapeutics. In this study, we evaluated the clinical usefulness of a novel tau-imaging positron emission tomography tracer 18F-THK5105 in 16 human subjects including eight patients with Alzheimer's disease (three male and five females, 66-82 years) and eight healthy elderly controls (three male and five females, 63-76 years). All participants underwent neuropsychological examination and 3D magnetic resonance imaging, as well as both 18F-THK5105 and 11C-Pittsburgh compound B positron emission tomography scans. Standard uptake value ratios at 90-100 min and 40-70 min post-injection were calculated for 18F-THK5105 and 11C-Pittsburgh compound B, respectively, using the cerebellar cortex as the reference region. As a result, significantly higher 18F-THK5105 retention was observed in the temporal, parietal, posterior cingulate, frontal and mesial temporal cortices of patients with Alzheimer's disease compared with healthy control subjects. In patients with Alzheimer's disease, the inferior temporal cortex, which is an area known to contain high densities of neurofibrillary tangles in the Alzheimer's disease brain, showed prominent 18F-THK5105 retention. Compared with high frequency (100%) of 18F-THK5105 retention in the temporal cortex of patients with Alzheimer's disease, frontal 18F-THK5105 retention was less frequent (37.5%) and was only observed in cases with moderate-to-severe Alzheimer's disease. In contrast, 11C-Pittsburgh compound B retention was highest in the posterior cingulate cortex, followed by the ventrolateral prefrontal, anterior cingulate, and superior temporal cortices, and did not correlate with 18F-THK5105 retention in the neocortex. In healthy control subjects, 18F-THK5105 retention was ∼10% higher in the mesial temporal cortex than in the neocortex. Notably, unlike 11C-Pittsburgh compound B, 18F-THK5105 retention was significantly correlated with cognitive parameters, hippocampal and whole brain grey matter volumes, which was consistent with findings from previous post-mortem studies showing significant correlations of neurofibrillary tangle density with dementia severity or neuronal loss. From these results, 18F-THK5105 positron emission tomography is considered to be useful for the non-invasive assessment of tau pathology in the living brain. This technique would be applicable to the longitudinal evaluation of tau deposition and allow a better understanding of the pathophysiology of Alzheimer's disease.

Objective: Biomarkers for Alzheimer disease (AD) can detect the disease pathology in asymptomatic subjects and individuals with mild cognitive impairment (MCI), but their cognitive prognosis remains uncertain. We aimed to determine the prognostic value of b-amyloid imaging, alone and in combination with memory performance, hippocampal atrophy, and apolipoprotein E e4 status in nondemented, older individuals. Methods: A total of 183 healthy individuals (age 5 72.0 6 7.26 years) and 87 participants with MCI (age 5 73.7 6 8.27) in the Australian Imaging, Biomarkers, and Lifestyle study of ageing were studied. Clinical reclassification was performed after 3 years, blind to biomarker findings. b-Amyloid imaging was considered positive if the 11 C-Pittsburgh compound B cortical to reference ratio was 1.5. Results: Thirteen percent of healthy persons progressed (15 to MCI, 8 to dementia), and 59% of the MCI cohort progressed to probable AD. Multivariate analysis showed b-amyloid imaging as the single variable most strongly associated with progression. Of combinations, subtle memory impairment (Z score 5 20.5 to 21.5) with a positive amyloid scan was most strongly associated with progression in healthy individuals (odds ratio [OR] 5 16, 95% confidence interval [CI] 5 3.7-68; positive predictive value [PPV] 5 50%, 95% CI 5 19-81; negative predictive value [NPV] 5 94%, 95% CI 5 88-98). Almost all amnestic MCI subjects (Z score 21.5) with a positive amyloid scan developed AD (OR 5 1; PPV 5 86%, 95% CI 5 72-95; NPV 5 100%, 95% CI 5 80-100). Hippocampal atrophy and e4 status did not add further predictive value.View this article online at wileyonlinelibrary.com.

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.