Study protocol: Insight 46 - a neuroscience sub-study of the MRC National Survey of Health and Development.

BACKGROUND: Increasing age is the biggest risk factor for dementia, of which Alzheimer's disease is the commonest cause. The pathological changes underpinning Alzheimer's disease are thought to develop at least a decade prior to the onset of symptoms. Molecular positron emission tomography and multi-modal magnetic resonance imaging allow key pathological processes underpinning cognitive impairment - including ß-amyloid depostion, vascular disease, network breakdown and atrophy - to be assessed repeatedly and non-invasively. This enables potential determinants of dementia to be delineated earlier, and therefore opens a pre-symptomatic window where intervention may prevent the onset of cognitive symptoms. METHODS/DESIGN: This paper outlines the clinical, cognitive and imaging protocol of "Insight 46", a neuroscience sub-study of the MRC National Survey of Health and Development. This is one of the oldest British birth cohort studies and has followed 5362 individuals since their birth in England, Scotland and Wales during one week in March 1946. These individuals have been tracked in 24 waves of data collection incorporating a wide range of health and functional measures, including repeat measures of cognitive function. Now aged 71 years, a small fraction have overt dementia, but estimates suggest that ~1/3 of individuals in this age group may be in the preclinical stages of Alzheimer's disease. Insight 46 is recruiting 500 study members selected at random from those who attended a clinical visit at 60-64 years and on whom relevant lifecourse data are available. We describe the sub-study design and protocol which involves a prospective two time-point (0, 24 month) data collection covering clinical, neuropsychological, ß-amyloid positron emission tomography and magnetic resonance imaging, biomarker and genetic information. Data collection started in 2015 (age 69) and aims to be completed in 2019 (age 73). DISCUSSION: Through the integration of data on the socioeconomic environment and on physical, psychological and cognitive function from 0 to 69 years, coupled with genetics, structural and molecular imaging, and intensive cognitive and neurological phenotyping, Insight 46 aims to identify lifetime factors which influence brain health and cognitive ageing, with particular focus on Alzheimer's disease and cerebrovascular disease. This will provide an evidence base for the rational design of disease-modifying trials.

Prominent effects and neural correlates of visual crowding in a neurodegenerative disease population.

Crowding is a breakdown in the ability to identify objects in clutter, and is a major constraint on object recognition. Crowding particularly impairs object perception in peripheral, amblyopic and possibly developing vision. Here we argue that crowding is also a critical factor limiting object perception in central vision of individuals with neurodegeneration of the occipital cortices. In the current study, individuals with posterior cortical atrophy (n=26), typical Alzheimer's disease (n=17) and healthy control subjects (n=14) completed centrally-presented tests of letter identification under six different flanking conditions (unflanked, and with letter, shape, number, same polarity and reverse polarity flankers) with two different target-flanker spacings (condensed, spaced). Patients with posterior cortical atrophy were significantly less accurate and slower to identify targets in the condensed than spaced condition even when the target letters were surrounded by flankers of a different category. Importantly, this spacing effect was observed for same, but not reverse, polarity flankers. The difference in accuracy between spaced and condensed stimuli was significantly associated with lower grey matter volume in the right collateral sulcus, in a region lying between the fusiform and lingual gyri. Detailed error analysis also revealed that similarity between the error response and the averaged target and flanker stimuli (but not individual target or flanker stimuli) was a significant predictor of error rate, more consistent with averaging than substitution accounts of crowding. Our findings suggest that crowding in posterior cortical atrophy can be regarded as a pre-attentive process that uses averaging to regularize the pathologically noisy representation of letter feature position in central vision. These results also help to clarify the cortical localization of feature integration components of crowding. More broadly, we suggest that posterior cortical atrophy provides a neurodegenerative disease model for exploring the basis of crowding. These data have significant implications for patients with, or who will go on to develop, dementia-related visual impairment, in whom acquired excessive crowding likely contributes to deficits in word, object, face and scene perception.

Propionibacterium acnes: an underestimated etiology in the pathogenesis of osteoarthritis?

BACKGROUND: Propionibacterium acnes is a common pathogen in infections after shoulder surgery. Recent reports found positive P acnes cultures in a high percentage of patients who had revision shoulder arthroplasty for "aseptic loosening" without any overt signs of infection. Isolation of P acnes is difficult, and by use of conventional microbiological protocols of 48-hour incubation, a considerable proportion of patients with possible P acnes infection may remain unidentified. We recently noted P acnes in shoulder joint cultures in patients undergoing primary shoulder replacement for glenohumeral arthropathy without any signs of infection. METHODS: We collected aspirates and biopsy specimens from 55 consecutive patients with arthritic shoulders undergoing primary joint replacement and examined them for the presence of P acnes. Special measures were taken to ensure that the specimens were carefully taken from within the joint to reduce the risk of contamination to minimal. RESULTS: In 23 of 55 consecutive patients (41.8%) undergoing primary shoulder joint replacement, P acnes was found in the joint fluid and tissues taken before the insertion of the implants. All these patients were treated early postoperatively with pathogen-directed specific dual oral antibiotic treatment for 4 weeks. In none have any signs of infection developed. DISCUSSION AND CONCLUSION: This finding of a high incidence of P acnes in joints before arthroplasty may suggest a role of P acnes in the pathogenesis of glenohumeral arthropathy. In addition, it raises the question of whether development of painful joint replacement later on and presumed aseptic loosening do, in fact, comprise an unrecognized low-grade infection that has been present since before the index operation.

Dissemination in time and space in presymptomatic granulin mutation carriers: a GENFI spatial chronnectome study.

The presymptomatic brain changes of granulin (GRN) disease, preceding by years frontotemporal dementia, has not been fully characterized. New approaches focus on the spatial chronnectome can capture both spatial network configurations and their dynamic changes over time. To investigate the spatial dynamics in 141 presymptomatic GRN mutation carriers and 282 noncarriers from the Genetic Frontotemporal dementia research Initiative cohort. We considered time-varying patterns of the default mode network, the language network, and the salience network, each summarized into 4 distinct recurring spatial configurations. Dwell time (DT) (the time each individual spends in each spatial state of each network), fractional occupacy (FO) (the total percentage of time spent by each individual in a state of a specific network) and total transition number (the total number of transitions performed by each individual in a specifict state) were considered. Correlations between DT, FO, and transition number and estimated years from expected symptom onset (EYO) and clinical performances were assessed. Presymptomatic GRN mutation carriers spent significantly more time in those spatial states characterised by greater activation of the insula and the parietal cortices, as compared to noncarriers (p < 0.05, FDR-corrected). A significant correlation between DT and FO of these spatial states and EYO was found, the longer the time spent in the spatial states, the closer the EYO. DT and FO significantly correlated with performances at tests tapping processing speed, with worse scores associated with increased spatial states' DT. Our results demonstrated that presymptomatic GRN disease presents a complex dynamic reorganization of brain connectivity. Change in both the spatial and temporal aspects of brain network connectivity could provide a unique glimpse into brain function and potentially allowing a more sophisticated evaluation of the earliest disease changes and the understanding of possible mechanisms in GRN disease.

(Con)text-specific effects of visual dysfunction on reading in posterior cortical atrophy.

Reading deficits are a common early feature of the degenerative syndrome posterior cortical atrophy (PCA) but are poorly understood even at the single word level. The current study evaluated the reading accuracy and speed of 26 PCA patients, 17 typical Alzheimer's disease (tAD) patients and 14 healthy controls on a corpus of 192 single words in which the following perceptual properties were manipulated systematically: inter-letter spacing, font size, length, font type, case and confusability. PCA reading was significantly less accurate and slower than tAD patients and controls, with performance significantly adversely affected by increased letter spacing, size, length and font (cursive < non-cursive), and characterised by visual errors (69% of all error responses). By contrast, tAD and control accuracy rates were at or near ceiling, letter spacing was the only perceptual factor to influence reading speed in the same direction as controls, and, in contrast to PCA patients, control reading was faster for larger font sizes. The inverse size effect in PCA (less accurate reading of large than small font size print) was associated with lower grey matter volume in the right superior parietal lobule. Reading accuracy was associated with impairments of early visual (especially crowding), visuoperceptual and visuospatial processes. However, these deficits were not causally related to a universal impairment of reading as some patients showed preserved reading for small, unspaced words despite grave visual deficits. Rather, the impact of specific types of visual dysfunction on reading was found to be (con)text specific, being particularly evident for large, spaced, lengthy words. These findings improve the characterisation of dyslexia in PCA, shed light on the causative and associative factors, and provide clear direction for the development of reading aids and strategies to maximise and sustain reading ability in the early stages of disease.

Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment.

Accurately identifying the patients that have mild cognitive impairment (MCI) who will go on to develop Alzheimer's disease (AD) will become essential as new treatments will require identification of AD patients at earlier stages in the disease process. Most previous work in this area has centred around the same automated techniques used to diagnose AD patients from healthy controls, by coupling high dimensional brain image data or other relevant biomarker data to modern machine learning techniques. Such studies can now distinguish between AD patients and controls as accurately as an experienced clinician. Models trained on patients with AD and control subjects can also distinguish between MCI patients that will convert to AD within a given timeframe (MCI-c) and those that remain stable (MCI-s), although differences between these groups are smaller and thus, the corresponding accuracy is lower. The most common type of classifier used in these studies is the support vector machine, which gives categorical class decisions. In this paper, we introduce Gaussian process (GP) classification to the problem. This fully Bayesian method produces naturally probabilistic predictions, which we show correlate well with the actual chances of converting to AD within 3 years in a population of 96 MCI-s and 47 MCI-c subjects. Furthermore, we show that GPs can integrate multimodal data (in this study volumetric MRI, FDG-PET, cerebrospinal fluid, and APOE genotype with the classification process through the use of a mixed kernel). The GP approach aids combination of different data sources by learning parameters automatically from training data via type-II maximum likelihood, which we compare to a more conventional method based on cross validation and an SVM classifier. When the resulting probabilities from the GP are dichotomised to produce a binary classification, the results for predicting MCI conversion based on the combination of all three types of data show a balanced accuracy of 74%. This is a substantially higher accuracy than could be obtained using any individual modality or using a multikernel SVM, and is competitive with the highest accuracy yet achieved for predicting conversion within three years on the widely used ADNI dataset.