Cerebral atrophy in mild cognitive impairment and Alzheimer disease: rates and acceleration.

OBJECTIVE: To quantify the regional and global cerebral atrophy rates and assess acceleration rates in healthy controls, subjects with mild cognitive impairment (MCI), and subjects with mild Alzheimer disease (AD). METHODS: Using 0-, 6-, 12-, 18-, 24-, and 36-month MRI scans of controls and subjects with MCI and AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we calculated volume change of whole brain, hippocampus, and ventricles between all pairs of scans using the boundary shift integral. RESULTS: We found no evidence of acceleration in whole-brain atrophy rates in any group. There was evidence that hippocampal atrophy rates in MCI subjects accelerate by 0.22%/year2 on average (p = 0.037). There was evidence of acceleration in rates of ventricular enlargement in subjects with MCI (p = 0.001) and AD (p < 0.001), with rates estimated to increase by 0.27 mL/year2 (95% confidence interval 0.12, 0.43) and 0.88 mL/year2 (95% confidence interval 0.47, 1.29), respectively. A post hoc analysis suggested that the acceleration of hippocampal loss in MCI subjects was mainly driven by the MCI subjects that were observed to progress to clinical AD within 3 years of baseline, with this group showing hippocampal atrophy rate acceleration of 0.50%/year2 (p = 0.003). CONCLUSIONS: The small acceleration rates suggest a long period of transition to the pathologic losses seen in clinical AD. The acceleration in hippocampal atrophy rates in MCI subjects in the ADNI seems to be driven by those MCI subjects who concurrently progressed to a clinical diagnosis of AD

Online clinical tools to support the use of new plasma biomarker diagnostic technology in the assessment of Alzheimer's disease: a narrative review

Recent advances in new diagnostic technologies for Alzheimer's disease have improved the speed and precision of diagnosis. However, accessing the potential benefits of this technology poses challenges for clinicians, such as deciding whether it is clinically appropriate to order a diagnostic test, which specific test or tests to order and how to interpret test results and communicate these to the patient and their caregiver. Tools to support decision-making could provide additional structure and information to the clinical assessment process. These tools could be accessed online, and such 'e-tools' can provide an interactive interface to support patients and clinicians in the use of new diagnostic technologies for Alzheimer's disease. We performed a narrative review of the literature to synthesize information available on this research topic. Relevant studies that provide an understanding of how these online tools could be used to optimize the clinical utility of diagnostic technology were identified. Based on these, we discuss the ways in which e-tools have been used to assist in the diagnosis of Alzheimer's disease and propose recommendations for future research to aid further development

Alzheimer's Disease Biomarkers Revisited From the Amyloid Cascade Hypothesis Standpoint

Alzheimer’s disease (AD) is the most common neurodegenerative disease worldwide. Amyloid beta (Aβ) is one of the proteins which aggregate in AD, and its key role in the disease pathogenesis is highlighted in the amyloid cascade hypothesis, which states that the deposition of Aβ in the brain parenchyma is a crucial initiating step in the future development of AD. The sensitivity of instruments used to measure proteins in blood and cerebrospinal fluid has significantly improved, such that Aβ can now successfully be measured in plasma. However, due to the peripheral production of Aβ, there is significant overlap between diagnostic groups. The presence of pathological Aβ within the AD brain has several effects on the cells and surrounding tissue. Therefore, there is a possibility that using markers of tissue responses to Aβ may reveal more information about Aβ pathology and pathogenesis than looking at plasma Aβ alone. In this manuscript, using the amyloid cascade hypothesis as a starting point, we will delve into how the effect of Aβ on the surrounding tissue can be monitored using biomarkers. In particular, we will consider whether glial fibrillary acidic protein, triggering receptor expressed on myeloid cells 2, phosphorylated tau, and neurofilament light chain could be used to phenotype and quantify the tissue response against Aβ pathology in AD

Knockdown of Amyloid Precursor Protein: Biological Consequences and Clinical Opportunities

Amyloid precursor protein (APP) and its cleavage fragment Amyloid-β (Aβ) have fundamental roles in Alzheimer’s disease (AD). Genetic alterations that either increase the overall dosage of APP or alter its processing to favour the generation of longer, more aggregation prone Aβ species, are directly causative of the disease. People living with one copy of APP are asymptomatic and reducing APP has been shown to lower the relative production of aggregation-prone Aβ species in vitro. For these reasons, reducing APP expression is an attractive approach for AD treatment and prevention. In this review, we will describe the structure and the known functions of APP and go on to discuss the biological consequences of APP knockdown and knockout in model systems. We highlight progress in therapeutic strategies to reverse AD pathology via reducing APP expression. We conclude that new technologies that reduce the dosage of APP expression may allow disease modification and slow clinical progression, delaying or even preventing onset

Structural neuroanatomy of tinnitus and hyperacusis in semantic dementia

Introduction Tinnitus and hyperacusis are common symptoms of excessive auditory perception in the general population; however, their anatomical substrates and disease associations continue to be defined. Patients with semantic dementia (SemD) frequently repor

A critical review of the epidemiological evidence of effects of air pollution on dementia, cognitive function and cognitive decline in adult population

Dementia is arguably the most pressing public health challenge of our age. Since dementia does not have a cure,identifying risk factors that can be controlled has become paramount to reduce the personal, societal and eco-nomic burden of dementia. The relationship between exposure to air pollution and effects on cognitive function,cognitive decline and dementia has stimulated increasing scientific interest in the past few years. This review ofthe literature critically examines the available epidemiological evidence of associations between exposure to am-bient air pollutants, cognitive performance, acceleration of cognitive decline, risk of developing dementia, neuro-imaging and neurological biomarker studies, following Bradford Hill guidelines for causality.The evidence reviewed has been consistent in reporting associations between chronic exposure to air pollutionand reduced global cognition, as well as impairment in specific cognitive domains including visuo-spatial abili-ties. Cognitive decline and dementia incidence have also been consistently associated with exposure to air pollu-tion. The neuro-imaging studies reviewed report associations between exposure to air pollution and whitematter volume reduction. Other reported effects include reduction in gray matter, larger ventricular volume,and smaller corpus callosum. Findings relating to ischemic (white matter hyperintensities/silent cerebralinfarcts) and hemorrhagic (cerebral microbleeds) markers of cerebral small vessel disease have been heteroge-neous, as have observations on hippocampal volume and air pollution. The few studies available on neuro-inflammation tend to report associations with exposure to air pollution. everal effect modifiers have been suggested in the literature, but more replication studies are required. Tradi-tional confounding factors have been controlled or adjusted for in most of the reviewed studies. Additional con-founding factors have also been considered, but the inclusion of these has varied among the different studies.Despite all the efforts to adjust for confounding factors, residual confounding cannot be completely ruled out, es-pecially since the factors affecting cognition and dementia are not yet fully understood.The available evidence meets many of the Bradford Hill guidelines for causality. The reported associations be-tween a range of air pollutants and effects oncognitive function in older people,including the acceleration of cog-nitive decline and the induction of dementia, are likely to be causal in nature.However, the diversity of study designs, air pollutants and endpoints examined precludes the attribution of theseadverse effects to a single class of pollutant and makes meta-analysis inappropriate

Imaging tau pathology in Alzheimer's disease with positron emission tomography: lessons learned from imaging-neuropathology validation studies

Though the presence of both amyloid-β (Aβ) plaques and tau neurofibrillary tangles is necessary for neuropathologic diagnosis of Alzheimer’s disease (AD), it is now widely recognized that tau burden correlates more strongly with neurodegeneration and cognitive impairment in life than the development of Aβ plaques [1]. Recent developments of tau-sensitive radiotracers for imaging with positron emission tomography (PET) have, for the first time, enabled visualisation, mapping, and quantification of inclusions of aggregated, paired helical filament (PHF) tau associated with AD in the living brain [2]. In-depth characterisation of tau PET tracers, and in particular comparison of antemortem PET readings with postmortem neuropathologic findings, were of paramount importance to understand the clinical potential and limitations of the new imaging tools. In the case of [18F]flortaucipir, the most widely used tau PET ligand, these cross-validation studies, together with autoradiography evaluations, provided information about the specificity of this tracer to PHF-tau in AD but also revealed substantial undesired (off-target) binding and limited ability to detect PHF-tau at the earliest Braak stages [3,4,5,6,7]. The combined data subsequently underpinned the implementation of an effective method for the clinical interpretation of [18F]flortaucipir PET scans [3]. Ultimately, these efforts have led to the approval of [(18)^F]flortaucipir by the US Food and Drug Administration (FDA) as the first PET radiopharmaceutical indicated to ‘estimate the density and distribution of aggregated neurofibrillary tangles in patients with cognitive impairment who are being evaluated for AD (Tauvid prescribing information, https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/212123s000lbl.pdf)

Data-driven modelling of neurodegenerative disease progression: thinking outside the black box

Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings

Long-Term Follow-Up of Patients Immunized with AN1792: Reduced Functional Decline in Antibody Responders

BACKGROUND: Immunization of patients with Alzheimer's disease (AD) with synthetic amyloid-beta peptide (Abeta(42)) (AN1792) was previously studied in a randomized, double-blind, placebo-controlled phase 2a clinical trial, Study AN1792(QS-21)-201. Treatment was discontinued following reports of encephalitis. One year follow-up revealed that AN1792 antibody responders showed improvements in cognitive measures as assessed by the neuropsychological test battery (NTB) and a decrease in brain volume compared with placebo. METHODS: A follow-up study, Study AN1792(QS-21)-251, was conducted to assess the long-term functional, psychometric, neuroimaging, and safety outcomes of patients from the phase 2a study 4.6 years after immunization with AN1792. The results were analyzed by comparing patients originally identified as antibody responders in the AN1792 phase 2a study with placebo-treated patients. RESULTS: One hundred and fifty-nine patients/caregivers (30 placebo; 129 AN1792) participated in this follow-up study. Of the 129 AN1792-treated patients, 25 were classified in the phase 2a study as antibody responders (anti-AN1792 titers > or = 1:2,200 at any time after the first injection). Low but detectable, sustained anti-AN1792 titers were found in 17 of 19 samples obtained from patients classified as antibody responders in the phase 2a study. No detectable anti-AN1792 antibodies were found in patients not classified as antibody responders in the phase 2a study. Significantly less decline was observed on the Disability Assessment for Dementia scale among antibody responders than placebo-treated patients (p=0.015) after 4.6 years. Significant differences in favor of responders were also observed on the Dependence Scale (p=0.033). Of the small number of patients who underwent a follow-up MRI, antibody responders showed similar brain volume loss during the follow-up period subsequent to the AN1792 phase 2a study compared with placebo-treated patients. CONCLUSIONS: Approximately 4.6 years after immunization with AN1792, patients defined as responders in the phase 2a study maintained low but detectable, sustained anti-AN1792 antibody titers and demonstrated significantly reduced functional decline compared with placebo-treated patients. Brain volume loss in antibody responders was not significantly different from placebo-treated patients approximately 3.6 years from the end of the original study. No further cases of encephalitis were noted. These data support the hypothesis that Abeta immunotherapy may have long-term functional benefits