Agrammatic but numerate

A central question in cognitive neuroscience concerns the extent to which language enables other higher cognitive functions. In the case of mathematics, the resources of the language faculty, both lexical and syntactic, have been claimed to be important for exact calculation, and some functional brain imaging studies have shown that calculation is associated with activation of a network of left-hemisphere language regions, such as the angular gyrus and the banks of the intraparietal sulcus. We investigate the integrity of mathematical calculations in three men with large left-hemisphere perisylvian lesions. Despite severe grammatical impairment and some difficulty in processing phonological and orthographic number words, all basic computational procedures were intact across patients. All three patients solved mathematical problems involving recursiveness and structure-dependent operations (for example, in generating solutions to bracket equations). To our knowledge, these results demonstrate for the first time the remarkable independence of mathematical calculations from language grammar in the mature cognitive system

Presymptomatic cortical thinning in familial Alzheimer disease: A longitudinal MRI study.

OBJECTIVE: To identify a cortical signature pattern of cortical thinning in familial Alzheimer disease (FAD) and assess its utility in detecting and tracking presymptomatic neurodegeneration. METHODS: We recruited 43 FAD mutation carriers-36 PSEN1, 7 APP (20 symptomatic, 23 presymptomatic)-and 42 healthy controls to a longitudinal clinical and MRI study. T1-weighted MRI scans were acquired at baseline in all participants; 55 individuals (33 mutation carriers; 22 controls) had multiple (mean 2.9) follow-up scans approximately annually. Cortical thickness was measured using FreeSurfer. A cortical thinning signature was identified from symptomatic FAD participants. We then examined cortical thickness changes in this signature region in presymptomatic carriers and assessed associations with cognitive performance. RESULTS: The cortical signature included 6 regions: entorhinal cortex, inferior parietal cortex, precuneus, superior parietal cortex, superior frontal cortex, and supramarginal gyrus. There were significant differences in mean cortical signature thickness between mutation carriers and controls 3 years before predicted symptom onset. The earliest significant difference in a single region, detectable 4 years preonset, was in the precuneus. Rate of change in cortical thickness became significantly different in the cortical signature at 5 years before predicted onset, and in the precuneus at 8 years preonset. Baseline mean signature thickness predicted rate of subsequent thinning and correlated with presymptomatic cognitive change. CONCLUSIONS: The FAD cortical signature appears to be similar to that described for sporadic AD. All component regions showed significant presymptomatic thinning. A composite signature may provide more robust results than a single region and have utility as an outcome measure in presymptomatic trials

Using florbetapir positron emission tomography to explore cerebrospinal fluid cut points and gray zones in small sample sizes

INTRODUCTION: We aimed to assess the feasibility of determining Alzheimer's disease cerebrospinal fluid (CSF) cut points in small samples through comparison with amyloid positron emission tomography (PET). METHODS: Twenty-three individuals (19 patients, four controls) had CSF measures of amyloid beta (Aβ)1-42 and total tau/Aβ1-42 ratio, and florbetapir PET. We compared CSF measures with visual and quantitative (standardized uptake value ratio [SUVR]) PET measures of amyloid. RESULTS: Seventeen of 23 were amyloid-positive on visual reads, and 14 of 23 at an SUVR of ≥1.1. There was concordance (positive/negative on both measures) in 20 of 23, of whom 19 of 20 were correctly classified at an Aβ1-42 of 630 ng/L, and 20 of 20 on tau/Aβ1-42 ratio (positive ≥0.88; negative ≤0.34). Three discordant cases had Aβ1-42 levels between 403 and 729 ng/L and tau/Aβ1-42 ratios of 0.54-0.58. DISCUSSION: Comparing amyloid PET and CSF biomarkers provides a means of assessing CSF cut points in vivo, and can be applied to small sample sizes. CSF tau/Aβ1-42 ratio appears robust at predicting amyloid status, although there are gray zones where there remains diagnostic uncertainty

Clinical and biomarker changes in dominantly inherited Alzheimer\u27s disease

BACKGROUND: The order and magnitude of pathologic processes in Alzheimer\u27s disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer\u27s disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease. METHODS: In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant\u27s age at baseline assessment and the parent\u27s age at the onset of symptoms of Alzheimer\u27s disease to calculate the estimated years from expected symptom onset (age of the participant minus parent\u27s age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes. RESULTS: Concentrations of amyloid-beta (Aβ) 42 in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset. CONCLUSIONS: We found that autosomal dominant Alzheimer\u27s disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer\u27s disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer\u27s disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease‐informed machine‐learning

Introduction Developing cross‐validated multi‐biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. Methods We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid‐PET and fluorodeoxyglucose positron‐emission tomography (FDG‐PET) to predict rates of cognitive decline. Prediction models were trained in autosomal‐dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross‐validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model‐based risk enrichment was estimated. Results A model combining all biomarker modalities and established in ADAD predicted the 4‐year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model‐based risk‐enrichment reduced the sample size required for detecting simulated intervention effects by 50%–75%. Discussion Our independently validated machine‐learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD

Clinical phenotype and genetic associations in autosomal dominant familial Alzheimer's disease: a case series.

BACKGROUND: The causes of phenotypic heterogeneity in familial Alzheimer's disease with autosomal dominant inheritance are not well understood. We aimed to characterise clinical phenotypes and genetic associations with APP and PSEN1 mutations in symptomatic autosomal dominant familial Alzheimer's disease (ADAD). METHODS: We retrospectively analysed genotypic and phenotypic data (age at symptom onset, initial cognitive or behavioural symptoms, and presence of myoclonus, seizures, pyramidal signs, extrapyramidal signs, and cerebellar signs) from all individuals with ADAD due to APP or PSEN1 mutations seen at the Dementia Research Centre in London, UK. We examined the frequency of presenting symptoms and additional neurological features, investigated associations with age at symptom onset, APOE genotype, and mutation position, and explored phenotypic differences between APP and PSEN1 mutation carriers. The proportion of individuals presenting with various symptoms was analysed with descriptive statistics, stratified by mutation type. FINDINGS: Between July 1, 1987, and Oct 31, 2015, age at onset was recorded for 213 patients (168 with PSEN1 mutations and 45 with APP mutations), with detailed history and neurological examination findings available for 121 (85 with PSEN1 mutations and 36 with APP mutations). We identified 38 different PSEN1 mutations (four novel) and six APP mutations (one novel). Age at onset differed by mutation, with a younger onset for individuals with PSEN1 mutations than for those with APP mutations (mean age 43·6 years [SD 7·2] vs 50·4 years [SD 5·2], respectively, p<0·0001); within the PSEN1 group, 72% of age at onset variance was explained by the specific mutation. A cluster of five mutations with particularly early onset (mean age at onset <40 years) involving PSEN1's first hydrophilic loop suggests critical functional importance of this region. 71 (84%) individuals with PSEN1 mutations and 35 (97%) with APP mutations presented with amnestic symptoms, making atypical cognitive presentations significantly more common in PSEN1 mutation carriers (n=14; p=0·037). Myoclonus and seizures were the most common additional neurological features; individuals with myoclonus (40 [47%] with PSEN1 mutations and 12 [33%] with APP mutations) were significantly more likely to develop seizures (p=0·001 for PSEN1; p=0·036 for APP), which affected around a quarter of the patients in each group (20 [24%] and nine [25%], respectively). A number of patients with PSEN1 mutations had pyramidal (21 [25%]), extrapyramidal (12 [14%]), or cerebellar (three [4%]) signs. INTERPRETATION: ADAD phenotypes are heterogeneous, with both age at onset and clinical features being influenced by mutation position as well as causative gene. This highlights the importance of considering genetic testing in young patients with dementia and additional neurological features in order to appropriately diagnose and treat their symptoms, and of examining different mutation types separately in future research. FUNDING: Medical Research Council and National Institute for Health Research