The neurology of ageing: what is normal?

Ageing is associated with changes in the nervous system with consequent alterations in some neurological examination findings: understanding what is 'normal' at different ages is essential when evaluating patients. In seminal papers published in 1931, Dr MacDonald Critchley summarised his observations and the prevailing evidence on the effects of ageing on, among others, sensation, reflexes, ocular function, olfaction, movement and cognition. In this review, these observations are re-evaluated in light of contemporary evidence. Factors influencing the measurement and interpretation of these clinical findings are then discussed, including reproducibility, the influence of comorbidities, secular trends, how 'normality' should best be defined, the problems of extrapolating group data to individuals and the influence of presymptomatic neurodegenerative disease states. The case is made that context is critical, and that combining life course data with detailed clinical and biomarker phenotyping is required to understand the determinants of normal neurological function associated with ageing

Chapter 6 - Cerebrospinal fluid in the dementias

Alzheimer disease, vascular dementia, dementia with Lewy bodies, and frontotemporal dementia are the most common central nervous system disorders that cause progressive neurocognitive dysfunction and ultimately dementia. A number of biomarkers for pathologies reflecting each condition have been developed. Here, we review these and give an overview of the current state of practice and research regarding cerebrospinal fluid biomarkers for these disorders. The chapter discusses both established (most of which are tau- and amyloid β-related) and upcoming biomarkers and details, wherever appropriate, clinical use and differential diagnostics aspects

Grip strength from midlife as an indicator of later-life brain health and cognition: evidence from a British birth cohort

Background: Grip strength is an indicator of physical function with potential predictive value for health in ageing populations. We assessed whether trends in grip strength from midlife predicted later-life brain health and cognition. Methods: 446 participants in an ongoing British birth cohort study, the National Survey of Health and Development (NSHD), had their maximum grip strength measured at ages 53, 60–64, and 69, and subsequently underwent neuroimaging as part of a neuroscience sub-study, referred to as “Insight 46”, at age 69–71. A group-based trajectory model identified latent groups of individuals in the whole NSHD cohort with below- or above-average grip strength over time, plus a reference group. Group assignment, plus standardised grip strength levels and change from midlife were each related to measures of whole-brain volume (WBV) and white matter hyperintensity volume (WMHV), plus several cognitive tests. Models were adjusted for sex, body size, head size (where appropriate), sociodemographics, and behavioural and vascular risk factors. Results: Lower grip strength from midlife was associated with smaller WBV and lower matrix reasoning scores at age 69–71, with findings consistent between analysis of individual time points and analysis of trajectory groups. There was little evidence of an association between grip strength and other cognitive test scores. Although greater declines in grip strength showed a weak association with higher WMHV at age 69–71, trends in the opposite direction were seen at individual time points with higher grip strength at ages 60–64, and 69 associated with higher WMHV. Conclusions: This study provides preliminary evidence that maximum grip strength may have value in predicting brain health. Future work should assess to what extent age-related declines in grip strength from midlife reflect concurrent changes in brain structure

Blood Biomarkers for Alzheimer's Disease: Much Promise, Cautious Progress

Biomarkers in Alzheimer's disease (AD) have the potential to allow early and more accurate diagnosis, predict disease progression, stratify individuals and track response to candidate therapies in drug trials. The first fluid biomarkers reflecting aspects of AD neuropathology were identified in cerebrospinal fluid (CSF) in the 1990s. Three CSF biomarkers (amyloid-β 1-42, total tau and phospho-tau) have consistently been shown to have diagnostic utility and are incorporated into the new diagnostic criteria for AD. These markers have also been shown in longitudinal studies to predict conversion of mild cognitive impairment to AD. However, a key issue with the use of CSF biomarkers as a screening test is the invasiveness of lumbar puncture. Over the last 20 years there has been an active quest for blood biomarkers, which could be easily acquired and tested repeatedly throughout the disease course. One approach to identifying such markers is to attempt to measure candidates that have already been identified in CSF. Until recently, this approach has been limited by assay sensitivity, but newer platforms now allow single molecule-level detection. Another approach is identification of candidates in large multiplex panels that allow for multiple analytes to be quantified in parallel. While both approaches show promise, to date no blood-based biomarker or combination of biomarkers has sufficient predictive value to have utility in clinical practice. In this review, an overview of promising blood protein candidates is provided, and the challenges of validating and converting these into practicable tests are discussed

Mild Parkinsonian Signs: A Systematic Review of Clinical, Imaging, and Pathological Associations

Mild parkinsonian signs (MPS) have been widely studied during the past 3 decades and proposed as a risk marker for neurodegenerative disease. This systematic review explores the epidemiology, clinical and prognostic associations, radiological features, and pathological findings associated with MPS in older adults free from neurodegenerative disease. We find that MPS as currently defined are strongly associated with increasing age and increased risk of development of Parkinson's disease (PD), all-cause dementia, disability, and death. Positive associations with later PD are found mainly in younger populations and those with other features of prodromal PD. There are currently no consistent radiological findings for MPS, and pathological studies have shown that MPS, at least in the oldest old, are often underpinned by mixed neuropathologies, including those associated with Alzheimer's disease, cerebrovascular disease, nigral neuronal loss, and Lewy bodies. Different subcategories of MPS appear to convey varying risk and specificity for PD and other outcomes. MPS overall are not specific for parkinsonian disorders and, although associated with increased risk of PD, can reflect multiple pathologies, particularly in older individuals. “Mild motor signs” appears a more appropriate term to avoid prognostic and pathological implications, and larger future studies to prospectively examine outcomes and associations of specific MPS subcategories are required

Aducanumab: a new phase in therapeutic development for Alzheimer’s disease?

On 7 June(,) the FDA approved aducanumab, the first new drug for Alzheimer’s disease in almost 20 years—and notably, the first drug with a putative disease‐modifying mechanism for the treatment of this devastating disorder, namely the removal of β‐amyloid (or Aβ) plaques from the brain

Current concepts and controversies in the pathogenesis of Parkinson’s disease dementia and Dementia with Lewy Bodies

Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB) are relentlessly progressive neurodegenerative disorders that are likely to represent two ends of a disease spectrum. It is well established that both are characterised pathologically by widespread cortical Lewy body deposition. However, until recently, the pathophysiological mechanisms leading to neuronal damage were not known. It was also not understood why some cells are particularly vulnerable in PDD/DLB, nor why some individuals show more aggressive and rapid dementia than others. Recent studies using animal and cell models as well as human post-mortem analyses have provided important insights into these questions. Here, we review recent developments in the pathophysiology in PDD/DLB. Specifically, we examine the role of pathological proteins other than α-synuclein, consider particular morphological and physiological features that confer vulnerabilities on some neurons rather than others, and finally examine genetic factors that may explain some of the heterogeneity between individuals with PDD/DLB

A simulation system for biomarker evolution in neurodegenerative disease

We present a framework for simulating cross-sectional or longitudinal biomarker data sets from neurodegenerative disease cohorts that reflect the temporal evolution of the disease and population diversity. The simulation system provides a mechanism for evaluating the performance of data-driven models of disease progression, which bring together biomarker measurements from large cross-sectional (or short term longitudinal) cohorts to recover the average population-wide dynamics. We demonstrate the use of the simulation framework in two different ways. First, to evaluate the performance of the Event Based Model (EBM) for recovering biomarker abnormality orderings from cross-sectional datasets. Second, to evaluate the performance of a differential equation model (DEM) for recovering biomarker abnormality trajectories from short-term longitudinal datasets. Results highlight several important considerations when applying data-driven models to sporadic disease datasets as well as key areas for future work. The system reveals several important insights into the behaviour of each model. For example, the EBM is robust to noise on the underlying biomarker trajectory parameters, under-sampling of the underlying disease time course and outliers who follow alternative event sequences. However, the EBM is sensitive to accurate estimation of the distribution of normal and abnormal biomarker measurements. In contrast, we find that the DEM is sensitive to noise on the biomarker trajectory parameters, resulting in an over estimation of the time taken for biomarker trajectories to go from normal to abnormal. This over estimate is approximately twice as long as the actual transition time of the trajectory for the expected noise level in neurodegenerative disease datasets. This simulation framework is equally applicable to a range of other models and longitudinal analysis techniques