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Current methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer's disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient's longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer's Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with >90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject's degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid 42 or the β-amyloid 42 /β-amyloid 40 ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer's disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer's disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer's Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid 42 /β-amyloid 40 , neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid 42 /β-amyloid 40 as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80-0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69-0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06-0.14 units of area under curve for cognitively unimpaired, and by 0.21-0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04-0.11 units of area under curve for cognitively unimpaired and 0.05-0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80-0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE , global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid 42 /β-amyloid 40 may be improved by age and APOE genotype., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Pathological alterations to the locus coeruleus, the major source of noradrenaline in the brain, are histologically evident in early stages of neurodegenerative diseases. Novel MRI approaches now provide an opportunity to quantify structural features of the locus coeruleus in vivo during disease progression. In combination with neuropathological biomarkers, in vivo locus coeruleus imaging could help to understand the contribution of locus coeruleus neurodegeneration to clinical and pathological manifestations in Alzheimer's disease, atypical neurodegenerative dementias and Parkinson's disease. Moreover, as the functional sensitivity of the noradrenergic system is likely to change with disease progression, in vivo measures of locus coeruleus integrity could provide new pathophysiological insights into cognitive and behavioural symptoms. Locus coeruleus imaging also holds the promise to stratify patients into clinical trials according to noradrenergic dysfunction. In this article, we present a consensus on how non-invasive in vivo assessment of locus coeruleus integrity can be used for clinical research in neurodegenerative diseases. We outline the next steps for in vivo, post-mortem and clinical studies that can lay the groundwork to evaluate the potential of locus coeruleus imaging as a biomarker for neurodegenerative diseases., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Mounting evidence indicates that the polygenic basis of late-onset Alzheimer's disease can be harnessed to identify individuals at greatest risk for cognitive decline. We have previously developed and validated a polygenic hazard score comprising of 31 single nucleotide polymorphisms for predicting Alzheimer's disease dementia age of onset. In this study, we examined whether polygenic hazard scores are associated with: (i) regional tracer uptake using amyloid PET; (ii) regional volume loss using longitudinal MRI; (iii) post-mortem regional amyloid-β protein and tau associated neurofibrillary tangles; and (iv) four common non-Alzheimer's pathologies. Even after accounting for APOE, we found a strong association between polygenic hazard scores and amyloid PET standard uptake volume ratio with the largest effects within frontal cortical regions in 980 older individuals across the disease spectrum, and longitudinal MRI volume loss within the entorhinal cortex in 607 older individuals across the disease spectrum. We also found that higher polygenic hazard scores were associated with greater rates of cognitive and clinical decline in 632 non-demented older individuals, even after controlling for APOE status, frontal amyloid PET and entorhinal cortex volume. In addition, the combined model that included polygenic hazard scores, frontal amyloid PET and entorhinal cortex volume resulted in a better fit compared to a model with only imaging markers. Neuropathologically, we found that polygenic hazard scores were associated with regional post-mortem amyloid load and neuronal neurofibrillary tangles, even after accounting for APOE, validating our imaging findings. Lastly, polygenic hazard scores were associated with Lewy body and cerebrovascular pathology. Beyond APOE, we show that in living subjects, polygenic hazard scores were associated with amyloid deposition and neurodegeneration in susceptible brain regions. Polygenic hazard scores may also be useful for the identification of individuals at the highest risk for developing multi-aetiological dementia.

See Vandenberghe and Schaeverbeke (doi:10.1093/awx065) for a scientific commentary on this article. A long-term goal of our field is to determine the sequence of pathological events, which ultimately lead to cognitive decline and dementia. In this study, we first assessed the patterns of brain tau tangle accumulation (measured with the positron emission tomography tracer 18F-AV-1451) associated with well-established Alzheimer's disease factors in a cohort including cognitively healthy elderly individuals and individuals at early symptomatic stages of Alzheimer's disease. We then explored highly associated patterns of greater 18F-AV-1451 binding and increased annualized change in cortical amyloid-β plaques measured as florbetapir positron emission tomography binding antecedent to 18F-AV-1451 positron emission tomography scans, and to what extent these multimodal pattern associations explained the variance in cognitive performance and clinical outcome measures, independently and jointly. We found that: (i) 18F-AV-1451 positron emission tomography retention was differentially associated with age, and cross-sectional florbetapir positron emission tomography retention, but not with years of education, gender, or APOE genotype; (ii) increased annualized change in florbetapir retention, antecedent to 18F-AV-1451 positron emission tomography scans, in the parieto-temporal and precuneus brain regions was associated with greater 18F-AV-1451 PET retention most prominently in the inferior temporal and inferior parietal regions in the full cohort, with florbetapir positive/negative-associated variability; and (iii) this 18F-AV-1451 positron emission tomography retention pattern significantly explained the variance in cognitive performance and clinical outcome measures, independent of the associated antecedent increased annualized change in florbetapir positron emission tomography retention. These findings are in agreement with the pathology literature, which suggests that tau tangles but not amyloid-β plaques correlate with cognition and clinical symptoms. Furthermore, non-local associations linking increased amyloid-β accumulation rates with increased tau deposition are of great interest and support the idea that the amyloid-β pathology might have remote effects in disease pathology spread potentially via the brain's intrinsic connectivity networks., (© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Patients with Alzheimer's disease have reduced cerebral blood flow measured by arterial spin labelling magnetic resonance imaging, but it is unclear how this is related to amyloid-β pathology. Using 182 subjects from the Alzheimer's Disease Neuroimaging Initiative we tested associations of amyloid-β with regional cerebral blood flow in healthy controls (n = 51), early (n = 66) and late (n = 41) mild cognitive impairment, and Alzheimer's disease with dementia (n = 24). Based on the theory that Alzheimer's disease starts with amyloid-β accumulation and progresses with symptoms and secondary pathologies in different trajectories, we tested if cerebral blood flow differed between amyloid-β-negative controls and -positive subjects in different diagnostic groups, and if amyloid-β had different associations with cerebral blood flow and grey matter volume. Global amyloid-β load was measured by florbetapir positron emission tomography, and regional blood flow and volume were measured in eight a priori defined regions of interest. Cerebral blood flow was reduced in patients with dementia in most brain regions. Higher amyloid-β load was related to lower cerebral blood flow in several regions, independent of diagnostic group. When comparing amyloid-β-positive subjects with -negative controls, we found reductions of cerebral blood flow in several diagnostic groups, including in precuneus, entorhinal cortex and hippocampus (dementia), inferior parietal cortex (late mild cognitive impairment and dementia), and inferior temporal cortex (early and late mild cognitive impairment and dementia). The associations of amyloid-β with cerebral blood flow and volume differed across the disease spectrum, with high amyloid-β being associated with greater cerebral blood flow reduction in controls and greater volume reduction in late mild cognitive impairment and dementia. In addition to disease stage, amyloid-β pathology affects cerebral blood flow across the span from controls to dementia patients. Amyloid-β pathology has different associations with cerebral blood flow and volume, and may cause more loss of blood flow in early stages, whereas volume loss dominates in late disease stages.

Amyloid-β accumulation in the brain is thought to be one of the earliest events in Alzheimer's disease, possibly leading to synaptic dysfunction, neurodegeneration and cognitive/functional decline. The earliest detectable changes seen with neuroimaging appear to be amyloid-β accumulation detected by (11)C-labelled Pittsburgh compound B positron emission tomography imaging. However, some individuals tolerate high brain amyloid-β loads without developing symptoms, while others progressively decline, suggesting that events in the brain downstream from amyloid-β deposition, such as regional brain atrophy rates, play an important role. The main purpose of this study was to understand the relationship between the regional distributions of increased amyloid-β and the regional distribution of increased brain atrophy rates in patients with mild cognitive impairment. To simultaneously capture the spatial distributions of amyloid-β and brain atrophy rates, we employed the statistical concept of parallel independent component analysis, an effective method for joint analysis of multimodal imaging data. Parallel independent component analysis identified significant relationships between two patterns of amyloid-β deposition and atrophy rates: (i) increased amyloid-β burden in the left precuneus/cuneus and medial-temporal regions was associated with increased brain atrophy rates in the left medial-temporal and parietal regions; and (ii) in contrast, increased amyloid-β burden in bilateral precuneus/cuneus and parietal regions was associated with increased brain atrophy rates in the right medial temporal regions. The spatial distribution of increased amyloid-β and the associated spatial distribution of increased brain atrophy rates embrace a characteristic pattern of brain structures known for a high vulnerability to Alzheimer's disease pathology, encouraging for the use of (11)C-labelled Pittsburgh compound B positron emission tomography measures as early indicators of Alzheimer's disease. These results may begin to shed light on the mechanisms by which amyloid-β deposition leads to neurodegeneration and cognitive decline and the development of a more specific Alzheimer's disease-specific imaging signature for diagnosis and use of this knowledge in the development of new anti-therapies for Alzheimer's disease.

Epilepsy is a prevalent childhood neurological disorder, but there are few prospective quantitative magnetic resonance imaging studies examining patterns of brain development compared to healthy controls. Controlled prospective investigations initiated at or near epilepsy onset would best characterize the nature, timing and course of neuroimaging abnormalities in paediatric epilepsy. In this study, we report the results of a deformation-based morphometry technique to examine baseline and 2-year prospective neurodevelopmental brain changes in children with new and recent onset localization-related epilepsies (n = 24) and idiopathic generalized epilepsies (n = 20) compared to healthy controls (n = 36). Children with epilepsy demonstrated differences from controls in baseline grey and white matter volumes suggesting antecedent anomalies in brain development, as well as abnormal patterns of prospective brain development that involved not only slowed white matter expansion, but also abnormalities of cortical grey matter development involving both greater and lesser volume changes compared to controls. Furthermore, abnormal neurodevelopmental changes extended outside the cortex affecting several subcortical structures including thalamus, cerebellum, brainstem and pons. Finally, there were significant differences between the epilepsy syndromes (localization-related epilepsies and idiopathic generalized epilepsies) with the idiopathic generalized epilepsies group showing a more disrupted pattern of brain structure both at baseline and over the 2-year interval.