Measuring Global Brain Atrophy with the Brain Volume/Cerebrospinal Fluid Index: Normative Values, Cut-Offs and Clinical Associations

A high fat, high sugar diet exacerbates persistent post-surgical pain and modifies the brain-microbiota-gut axis in adolescent rats

Persistent post-surgical pain (PPSP) occurs in a proportion of patients following surgical interventions. Research suggests that specific microbiome components are important for brain development and function, with recent studies demonstrating that chronic pain results in changes to the microbiome. Consumption of a high fat, high sugar (HFHS) diet can drastically alter composition of the microbiome and is a modifiable risk factor for many neuroinflammatory conditions. Therefore, we investigated how daily consumption of a HFHS diet modified the development of PPSP, brain structure and function, and the microbiome. In addition, we identified significant correlations between the microbiome and brain in animals with PPSP. Male and female rats were maintained on a control or HFHS diet. Animals were further allocated to a sham or surgery on postnatal day (p) p35. The von Frey task measured mechanical nociceptive sensitivity at a chronic timepoint (p65-67). Between p68-72 rats underwent in-vivo MRI to examine brain volume and diffusivity. At p73 fecal samples were used for downstream 16 s rRNA sequencing. Spearman correlation analyses were performed between individual microbial abundance and MRI diffusivity to determine if specific bacterial species were associated with PPSP-induced brain changes. We found that consumption of a HFHS diet exacerbated PPSP in adolescents. The HFHS diet reduced overall brain volume and increased white and grey matter density. The HFHS diet interacted with the surgical intervention to modify diffusivity in numerous brain regions which were associated with specific changes to the microbiome. These findings demonstrate that premorbid characteristics can influence the development of PPSP and advance our understanding of the contribution that the microbiome has on function of the brain-microbiota-gut axis.

TransferGWAS of T1-weighted brain MRI data from UK Biobank

Genome-wide association studies (GWAS) traditionally analyze single traits, e.g., disease diagnoses or biomarkers. Nowadays, large-scale cohorts such as UK Biobank (UKB) collect imaging data with sample sizes large enough to perform genetic association testing. Typical approaches to GWAS on high-dimensional modalities extract predefined features from the data, e.g., volumes of regions of interest. This limits the scope of such studies to predefined traits and can ignore novel patterns present in the data. TransferGWAS employs deep neural networks (DNNs) to extract low-dimensional representations of imaging data for GWAS, eliminating the need for predefined biomarkers. Here, we apply transferGWAS on brain MRI data from UKB. We encoded 36, 311 T1-weighted brain magnetic resonance imaging (MRI) scans using DNN models trained on MRI scans from the Alzheimer's Disease Neuroimaging Initiative, and on natural images from the ImageNet dataset, and performed a multivariate GWAS on the resulting features. We identified 289 independent loci, associated among others with bone density, brain, or cardiovascular traits, and 11 regions having no previously reported associations. We fitted polygenic scores (PGS) of the deep features, which improved predictions of bone mineral density and several other traits in a multi-PGS setting, and computed genetic correlations with selected phenotypes, which pointed to novel links between diffusion MRI traits and type 2 diabetes. Overall, our findings provided evidence that features learned with DNN models can uncover additional heritable variability in the human brain beyond the predefined measures, and link them to a range of non-brain phenotypes.

Structural indices of brain aging in methamphetamine use disorder

BACKGROUND

Methamphetamine use is surging globally. It has been linked to premature stroke, Parkinsonism, and dementia, suggesting that it may accelerate brain aging.

METHODS

We performed a retrospective study to determine if structural indices of brain aging were more prevalent prior to old age (26 - 54 years) in individuals with Methamphetamine Use Disorder (MUD), who were in early abstinence (M ± SD = 22.1 ± 25.6 days) than in healthy control (HC) participants. We compared T1-weighted MRI brain scans in age- and sex-matched groups (n = 89/group) on three structural features of brain aging: the brain volume/cerebrospinal fluid (BV/CSF) index, volume of white matter hypointensities/lesions, and choroid plexus volume.

RESULTS

The MUD group had a lower mean BV/CSF index and larger volumes of white matter hypointensities and choroid plexus (p-values < 0.01). Regression analyses showed significant age-by-group effects, indicating different age trajectories of the BV/CSF index and choroid plexus volume, consistent with abnormal global brain atrophy and choroid plexus pathology in the MUD group. Significant age and group main effects reflected a larger volume of white matter hypointensities for older participants across groups and for the MUD group irrespective of age. None of the three measures of brain aging correlated significantly with recent use or duration of recent abstinence from methamphetamine.

CONCLUSIONS

Premature brain pathology, which may reflect cerebrovascular damage and dysfunction of the choroid plexus, occurs in people with MUD. Such pathology may affect cognition and thereby efficacy of behavioral treatments for MUD.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration

INTRODUCTION

Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification.

MATERIALS AND METHODS

We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition.

RESULTS

CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration.

DISCUSSION

These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation.

HIGHLIGHTS

Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Differential response to donepezil in MRI subtypes of mild cognitive impairment

BACKGROUND

Donepezil is an approved therapy for the treatment of Alzheimer's disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes.

METHODS

From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6-12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We primarily applied a subtyping approach based on continuous scale of two subtyping dimensions. We also used the conventional categorical subtyping approach for comparison.

RESULTS

Donepezil-treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal-sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response.

CONCLUSIONS

Our data suggest that individuals with MCI, with hippocampal-sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic-predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment.

TRIAL REGISTRATION

ClinicalTrial.gov NCT00403520. Submission Date: November 21, 2006.

Education differentiates cognitive performance and resting state fMRI connectivity in healthy aging

Objectives

In healthy aging, the way people cope differently with cognitive and neural decline is influenced by exposure to cognitively enriching life-experiences. Education is one of them, so that in general, the higher the education, the better the expected cognitive performance in aging. At the neural level, it is not clear yet how education can differentiate resting state functional connectivity profiles and their cognitive underpinnings. Thus, with this study, we aimed to investigate whether the variable education allowed for a finer description of age-related differences in cognition and resting state FC.

Methods

We analyzed in 197 healthy individuals (137 young adults aged 20-35 and 60 older adults aged 55-80 from the publicly available LEMON database), a pool of cognitive and neural variables, derived from magnetic resonance imaging, in relation to education. Firstly, we assessed age-related differences, by comparing young and older adults. Then, we investigated the possible role of education in outlining such differences, by splitting the group of older adults based on their education.

Results

In terms of cognitive performance, older adults with higher education and young adults were comparable in language and executive functions. Interestingly, they had a wider vocabulary compared to young adults and older adults with lower education. Concerning functional connectivity, the results showed significant age- and education-related differences within three networks: the Visual-Medial, the Dorsal Attentional, and the Default Mode network (DMN). For the DMN, we also found a relationship with memory performance, which strengthen the evidence that this network has a specific role in linking cognitive maintenance and FC at rest in healthy aging.

Discussion

Our study revealed that education contributes to differentiating cognitive and neural profiles in healthy older adults. Also, the DMN could be a key network in this context, as it may reflect some compensatory mechanisms relative to memory capacities in older adults with higher education.

Morphological evaluation of the normal and hydrocephalic third ventricle on cranial magnetic resonance imaging in children: a retrospective study

BACKGROUND

Third ventricle morphological changes reflect changes in the ventricular system in pediatric hydrocephalus, so visual inspection of the third ventricle shape is standard practice. However, normal pediatric reference data are not available.

OBJECTIVE

To investigate both the normal development of the third ventricle in the 0-18-year age group and changes in its biometry due to hydrocephalus.

MATERIALS AND METHODS

For this retrospective study, we selected individuals ages 0-18 years who had magnetic resonance imaging (MRI) from 2012 to 2020. We included 700 children (331 girls) who had three-dimensional (3-D) T1-weighted sequences without and 25 with hydrocephalus (11 girls). We measured the distances between the anatomical structures limiting the third ventricle by dividing the third ventricle into anterior and posterior regions. We made seven linear measurements and three index calculations using 3DSlicer and MRICloud pipeline, and we analyzed the results of 23 age groups in normal and hydrocephalic patients using SPSS (v. 23).

RESULTS

Salient findings are: (1) The posterior part of the third ventricle is more affected by both developmental and hydrocephalus-related changes. (2) For third ventricle measurements, gender was insignificant while age was significant. (3) Normal third ventricular volumetric development showed a segmental increase in the 0-18 age range. The hydrocephalic third ventricle volume cut-off value in this age group was 3 cm³.

CONCLUSION

This study describes third ventricle morphometry using a linear measurement method. The ratios defined in the midsagittal plane were clinically useful for diagnosing the hydrocephalic third ventricle. The linear and volumetric reference data and ratios are expected to help increase diagnostic accuracy in distinguishing normal and hydrocephalic third ventricles.

Neuropathologic Features of Antemortem Atrophy-Based Subtypes of Alzheimer Disease

BACKGROUND AND OBJECTIVES

To investigate whether antemortem MRI-based atrophy subtypes of Alzheimer disease (AD) differ in neuropathologic features and comorbid non-AD pathologies at postmortem.

METHODS

From the Alzheimer's Disease Neuroimaging Initiative cohort, we included individuals with antemortem MRI evaluating brain atrophy within 2 years before death, antemortem diagnosis of AD dementia/mild cognitive impairment, and postmortem-confirmed AD neuropathologic change. Antemortem atrophy subtypes were modeled as continuous phenomena based on a recent conceptual framework: typicality (spanning limbic-predominant AD to hippocampal-sparing AD) and severity (spanning typical AD to minimal atrophy AD). Postmortem neuropathologic evaluation included AD hallmarks, β-amyloid, and tau as well as non-AD pathologies, alpha-synuclein and TAR DNA-binding protein 43 (TDP-43). We also investigated the overall concomitance across these pathologies. Partial correlations assessed the associations between antemortem atrophy subtypes and postmortem neuropathologic outcomes.

RESULTS

In 31 individuals (26 AD dementia/5 mild cognitive impairment, mean age = 80 years, 26% females), antemortem typicality was significantly negatively associated with neuropathologic features, including β-amyloid (rho = -0.39 overall), tau (rho = -0.38 regionally), alpha-synuclein (rho = -0.39 regionally), TDP-43 (rho = -0.49 overall), and concomitance of pathologies (rho = -0.59 regionally). Limbic-predominant AD was associated with higher Thal phase, neuritic plaque density, and presence of TDP-43 compared with hippocampal-sparing AD. Regionally, limbic-predominant AD showed a higher presence of tau and alpha-synuclein pathologies in medial temporal structures, a higher presence of TDP-43, and concomitance of pathologies subcortically/cortically compared with hippocampal-sparing AD. Antemortem severity was significantly negatively associated with concomitance of pathologies (rho = -0.43 regionally), such that typical AD showed higher concomitance of pathologies than minimal atrophy AD.

DISCUSSION

We provide a direct antemortem-to-postmortem validation, highlighting the importance of understanding atrophy-based heterogeneity in AD relative to AD and non-AD pathologies. We suggest that (1) typicality and severity in atrophy reflect differential aspects of susceptibility of the brain to AD and non-AD pathologies; and (2) limbic-predominant AD and typical AD subtypes share similar biological pathways, making them more vulnerable to AD and non-AD pathologies compared with hippocampal-sparing AD, which may follow a different biological pathway. Our findings provide a deeper understanding of associations of atrophy subtypes in AD with different pathologies, enhancing the prevailing knowledge of biological heterogeneity in AD and could contribute toward tracking disease progression and designing clinical trials in the future.

Thirteen Independent Genetic Loci Associated with Preserved Processing Speed in a Study of Cognitive Resilience in 330,097 Individuals in the UK Biobank

Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. The UK Biobank does not have measurements of the same cognitive phenotype at distal time points. Therefore, we used education years (EY) as a proxy phenotype for past cognitive performance and current cognitive performance was based on processing speed. This represented an average time span of 40 years between past and current cognitive performance in 330,097 individuals. A confounding factor was that EY is highly polygenic and masked the genetics of resilience. To overcome this, we employed Genomics Structural Equation Modelling (GenomicSEM) to perform a genome-wide association study (GWAS)-by-subtraction using two GWAS, one GWAS of EY and resilience and a second GWAS of EY but not resilience, to generate a GWAS of Resilience. Using independent discovery and replication samples, we found 13 independent genetic loci for Resilience. Functional analyses showed enrichment in several brain regions and specific cell types. Gene-set analyses implicated the biological process "neuron differentiation", the cellular component "synaptic part" and the "WNT signalosome". Mendelian randomisation analysis showed a causative effect of white matter volume on cognitive resilience. These results may contribute to the neurobiological understanding of resilience.

Axonal plasma membrane-mediated toxicity of cholesterol in Alzheimer's disease: A microsecond molecular dynamics study

Alzheimer's disease is increasingly being recognized as an immune-mediated disease of brain. Since physiological brain health and brain immune function is dependent upon homeostatic neuronal membrane structure and function, alterations in membrane lipid biochemistry may predispose to disease. Brain is rich in cholesterol, and cholesterol metabolism dysfunction is a known risk factor for AD. Employing extensive microsecond all-atom molecular dynamics simulations, we investigated the properties of model neuronal membranes as a function of cholesterol concentration; phospholipid and phospholipid/cholesterol bilayers were also simulated to compare against available experimental data. Increased cholesterol concentrations compact and stiffen the lipid membrane, reducing permeability while modulating local water densities in the peri-membranous environment. Conversely, lower cholesterol mole fraction yields membranes with increased molecular disorder, enhanced fluidity, higher molecular tilting, and augmented interdigitation between bilayer leaflet lipids. Our findings provide a molecular insight on effect of cholesterol composition on various biochemical processes occurring at neuronal axon plasma membrane. These calculations also endeavor to establish a membrane-based link between cholesterol as an AD risk factor and possible AD pathology.

Assessment of Tau Pathology as Measured by 18F-THK5317 and 18F-Flortaucipir PET and Their Relation to Brain Atrophy and Cognition in Alzheimer's Disease

BACKGROUND

In Alzheimer's disease (AD), the abnormal aggregation of hyperphosphorylated tau leads to synaptic dysfunction and neurodegeneration. Recently developed tau PET imaging tracers are candidate biomarkers for diagnosis and staging of AD.

OBJECTIVE

We aimed to investigate the discriminative ability of 18F-THK5317 and 18F-flortaucipir tracers and brain atrophy at different stages of AD, and their respective associations with cognition.

METHODS

Two cohorts, each including 29 participants (healthy controls [HC], prodromal AD, and AD dementia patients), underwent 18F-THK5317 or 18F-flortaucipir PET, T1-weighted MRI, and neuropsychological assessment. For each subject, we quantified regional 18F-THK5317 and 18F-flortaucipir uptake within six bilateral and two composite regions of interest. We assessed global brain atrophy for each individual by quantifying the brain volume index, a measure of brain volume-to-cerebrospinal fluid ratio. We then quantified the discriminative ability of regional 18F-THK5317, 18F-flortaucipir, and brain volume index between diagnostic groups, and their associations with cognition in patients.

RESULTS

Both 18F-THK5317 and 18F-flortaucipir outperformed global brain atrophy in discriminating between HC and both prodromal AD and AD dementia groups. 18F-THK5317 provided the highest discriminative ability between HC and prodromal AD groups. 18F-flortaucipir performed best at discriminating between prodromal and dementia stages of AD. Across all patients, both tau tracers were predictive of RAVL learning, but only 18F-flortaucipir predicted MMSE.

CONCLUSION

Our results warrant further in vivo head-to-head and antemortem-postmortem evaluations. These validation studies are needed to select tracers with high clinical validity as biomarkers for early diagnosis, prognosis, and disease staging, which will facilitate their incorporation in clinical practice and therapeutic trials.

Cholinergic dysfunction, neurodegeneration, and amyloid-beta pathology in neurodegenerative diseases

Cholinergic dysfunction is central in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB). The electroencephalography-based acetylcholine index (EEG-Ach index) has been proposed as a biomarker of cholinergic dysfunction. However, it is unclear how the EEG-Ach index relates to amyloid-beta pathology and neurodegeneration. We investigated the association between the EEG-Ach index and cerebrospinal fluid (CSF) amyloid-beta, CSF total tau, cortical thickness, and hippocampal volume from magnetic resonance imaging (MRI), and cognition. A total of 127 patients with different neurodegenerative diseases were studied. The EEG-Ach index was calculated from quantitative EEG using statistical pattern recognition. The EEG-Ach index was associated with hippocampal volume and cortical thickness in frontal, temporal, and occipital cortices. Cross-sectional sub-analyses based on a small sample suggests that the EEG-Ach index increases the closest to AD dementia, downstream to amyloid-beta pathology, CSF total tau, and hippocampal volume. We conclude that cholinergic dysfunction correlates with atrophy in brain areas important for AD pathogenesis, and this association is more prominent in the dementia stage. These results together with previous studies from this project suggest that the EEG-Ach index may be a useful biomarker for cholinergic dysfunction, with value for differential diagnosis of dementia and monitoring patients at the dementia stage.

Subjective Cognitive Decline Below and Above the Age of 60: A Multivariate Study on Neuroimaging, Cognitive, Clinical, and Demographic Measures

Subjective cognitive complaints in cognitively normal individuals are a relevant predictor of Alzheimer's disease (AD), cerebrovascular disease, and age-related tauopathy. Complaints starting after the age of 60 increase the likelihood of preclinical AD. However, this criterion is arbitrary and current data show that neurodegenerative disorders likely start before that age. Further, data on the role of subjective complaints below the age of 60 in individuals qualifying for subjective cognitive decline (SCD) are lacking. We investigated the association of subjective cognitive complaints with an extensive number of neuroimaging, demographic, clinical, and cognitive measures in individuals fulfilling criteria for SCD below and above the age of 60. Nine complaints were scored in 416 individuals. Complaints were related to a higher load of white matter signal abnormalities, and this association was stronger the more subclinical changes in personality, interest, and drive were reported. In individuals <60 years, complaints were associated with lower global cognitive performance. In individuals ≥60 years, complaints were related to greater global brain atrophy and smaller total intracranial volume, and this association was stronger the more subclinical difficulties in activities of daily living were reported. Also, complaints were associated with increased depressive symptomatology irrespective of age. We conclude that complaints below the age of 60 may be associated with subtle signs of brain pathology. In the community, screening for risk of future cognitive decline should include subjective cognitive complaints, depressive symptomatology, and subclinical reduced cognition (<60 years)/activities of daily living (≥60 years), supported by basic neuroimaging examinations.

Application of Machine Learning to Automated Analysis of Cerebral Edema in Large Cohorts of Ischemic Stroke Patients

Cerebral edema contributes to neurological deterioration and death after hemispheric stroke but there remains no effective means of preventing or accurately predicting its occurrence. Big data approaches may provide insights into the biologic variability and genetic contributions to severity and time course of cerebral edema. These methods require quantitative analyses of edema severity across large cohorts of stroke patients. We have proposed that changes in cerebrospinal fluid (CSF) volume over time may represent a sensitive and dynamic marker of edema progression that can be measured from routinely available CT scans. To facilitate and scale up such approaches we have created a machine learning algorithm capable of segmenting and measuring CSF volume from serial CT scans of stroke patients. We now present results of our preliminary processing pipeline that was able to efficiently extract CSF volumetrics from an initial cohort of 155 subjects enrolled in a prospective longitudinal stroke study. We demonstrate a high degree of reproducibility in total cranial volume registration between scans (R = 0.982) as well as a strong correlation of baseline CSF volume and patient age (as a surrogate of brain atrophy, R = 0.725). Reduction in CSF volume from baseline to final CT was correlated with infarct volume (R = 0.715) and degree of midline shift (quadratic model, p < 2.2 × 10⁻¹⁶). We utilized generalized estimating equations (GEE) to model CSF volumes over time (using linear and quadratic terms), adjusting for age. This model demonstrated that CSF volume decreases over time (p < 2.2 × 10⁻¹³) and is lower in those with cerebral edema (p = 0.0004). We are now fully automating this pipeline to allow rapid analysis of even larger cohorts of stroke patients from multiple sites using an XNAT (eXtensible Neuroimaging Archive Toolkit) platform. Data on kinetics of edema across thousands of patients will facilitate precision approaches to prediction of malignant edema as well as modeling of variability and further understanding of genetic variants that influence edema severity.

Cerebrospinal Fluid Biomarkers for the Differential Diagnosis between Alzheimer's Disease and Frontotemporal Lobar Degeneration: Systematic Review, HSROC Analysis, and Confounding Factors

BACKGROUND

Differential diagnosis in dementia is at present one of the main challenges both in clinical practice and research. Cerebrospinal fluid (CSF) biomarkers are included in the current diagnostic criteria of Alzheimer's disease (AD) but their clinical utility is still unclear.

OBJECTIVE

We performed a systematic review of studies analyzing the diagnostic performance of CSF Aβ42, total tau (t-tau), and phosphorylated tau (p-tau) in the discrimination between AD and frontotemporal lobar degeneration (FTLD) dementias.

METHODS

The following electronic databases were consulted until May 2016: Medline and PreMedline, EMBASE, PsycInfo, CINAHL, Cochrane Library, and CRD. For the first-time in the field, a Hierarchical Summary Receiver Operating Characteristic (HRSOC) model was applied, which avoids methodological problems of meta-analyses based on summary points of sensitivity and specificity values. We also investigated relevant confounders of CSF biomarkers' diagnostic performance such as age, disease duration, and global cognitive impairment.

RESULTS

The p-tau/Aβ42 ratio showed the best diagnostic performance. No statistically significant effects of the confounders were observed. Nonetheless, the p-tau/Aβ42 ratio may be especially indicated for younger patients. P-tau may be preferable for less cognitively impaired patients (high MMSE scores) and the t-tau/Aβ42 ratio for more cognitively impaired patients (low MMSE scores).

CONCLUSION

The p-tau/Aβ42 ratio has potential for being implemented in the clinical routine for the differential diagnosis between AD and FTLD. It is of utmost importance that future studies report information on confounders such as age, disease duration, and cognitive impairment, which should also stimulate understanding of the role of these factors in disease mechanisms and pathophysiology.

Monitoring disease progression in mild cognitive impairment: Associations between atrophy patterns, cognition, APOE and amyloid

BACKGROUND

A disease severity index (SI) for Alzheimer's disease (AD) has been proposed that summarizes MRI-derived structural measures into a single score using multivariate data analysis.

OBJECTIVES

To longitudinally evaluate the use of the SI to monitor disease progression and predict future progression to AD in mild cognitive impairment (MCI). Further, to investigate the association between longitudinal change in the SI and cognitive impairment, Apolipoprotein E (APOE) genotype as well as the levels of cerebrospinal fluid amyloid-beta 1-42 (Aβ) peptide.

METHODS

The dataset included 195 AD, 145 MCI and 228 control subjects with annual follow-up for three years, where 70 MCI subjects progressed to AD (MCI-p). For each subject the SI was generated at baseline and follow-ups using 55 regional cortical thickness and subcortical volumes measures that extracted by the FreeSurfer longitudinal stream.

RESULTS

MCI-p subjects had a faster increase of the SI over time (p < 0.001). A higher SI at baseline in MCI-p was related to progression to AD at earlier follow-ups (p < 0.001) and worse cognitive impairment (p < 0.001). AD-like MCI patients with the APOE ε4 allele and abnormal Aβ levels had a faster increase of the SI, independently (p = 0.003 and p = 0.004).

CONCLUSIONS

Longitudinal changes in the SI reflect structural brain changes and can identify MCI patients at risk of progression to AD. Disease-related brain structural changes are influenced independently by APOE genotype and amyloid pathology. The SI has the potential to be used as a sensitive tool to predict future dementia, monitor disease progression as well as an outcome measure for clinical trials.

Distinct subtypes of Alzheimer's disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications

Atrophy patterns on MRI can reliably predict three neuropathological subtypes of Alzheimer’s disease (AD): typical, limbic-predominant, or hippocampal-sparing. A method to enable their investigation in the clinical routine is still lacking. We aimed to (1) validate the combined use of visual rating scales for identification of AD subtypes; (2) characterise these subtypes at baseline and over two years; and (3) investigate how atrophy patterns and non-memory cognitive domains contribute to memory impairment. AD patients were classified as either typical AD (n = 100), limbic-predominant (n = 33), or hippocampal-sparing (n = 35) by using the Scheltens’ scale for medial temporal lobe atrophy (MTA), the Koedam’s scale for posterior atrophy (PA), and the Pasquier’s global cortical atrophy scale for frontal atrophy (GCA-F). A fourth group with no atrophy was also identified (n = 30). 230 healthy controls were also included. There was great overlap among subtypes in demographic, clinical, and cognitive variables. Memory performance was more dependent on non-memory cognitive functions in hippocampal-sparing and the no atrophy group. Hippocampal-sparing and the no atrophy group showed less aggressive disease progression. Visual rating scales can be used to identify distinct AD subtypes. Recognizing AD heterogeneity is important and visual rating scales may facilitate investigation of AD heterogeneity in clinical routine.

Targeted delivery of nerve growth factor to the cholinergic basal forebrain of Alzheimer's disease patients: application of a second-generation encapsulated cell biodelivery device

Background

Targeted delivery of nerve growth factor (NGF) has emerged as a potential therapy for Alzheimer’s disease (AD) due to its regenerative effects on basal forebrain cholinergic neurons. This hypothesis has been tested in patients with AD using encapsulated cell biodelivery of NGF (NGF-ECB) in a first-in-human study. We report our results from a third-dose cohort of patients receiving second-generation NGF-ECB implants with improved NGF secretion.

Methods

Four patients with mild to moderate AD were recruited to participate in an open-label, phase Ib dose escalation study with a 6-month duration. Each patient underwent stereotactic implant surgery with four NGF-ECB implants targeted at the cholinergic basal forebrain. The NGF secretion of the second-generation implants was improved by using the Sleeping Beauty transposon gene expression technology and an improved three-dimensional internal scaffolding, resulting in production of about 10 ng NGF/device/day.

Results

All patients underwent successful implant procedures without complications, and all patients completed the study, including implant removal after 6 months. Upon removal, 13 of 16 implants released NGF, 8 implants released NGF at the same rate or higher than before the implant procedure, and 3 implants failed to release detectable amounts of NGF. Of 16 adverse events, none was NGF-, or implant-related. Changes from baseline values of cholinergic markers in cerebrospinal fluid (CSF) correlated with cortical nicotinic receptor expression and Mini Mental State Examination score. Levels of neurofilament light chain (NFL) protein increased in CSF after NGF-ECB implant, while glial fibrillary acidic protein (GFAP) remained stable.

Conclusions

The data derived from this patient cohort demonstrate the safety and tolerability of sustained NGF release by a second-generation NGF-ECB implant to the basal forebrain, with uneventful surgical implant and removal of NGF-ECB implants in a new dosing cohort of four patients with AD.

Trial registration

ClinicalTrials.gov identifier: NCT01163825. Registered on 14 Jul 2010.