Age-specific prevalence of the different clinical presentations of AD and FTD in young-onset dementia

BACKGROUND

Studies have shown that the prevalence of all-variants Alzheimer's disease (AD) and frontotemporal dementia (FTD) both increase with age, even before the age of 65. However, it is not known whether their different clinical presentations all increase in prevalence with age in the same way.

METHODS

We studied the prevalence of the different clinical presentations of young-onset AD and FTD by 5-year age groups in a population-based study identifying all dementia patients with a diagnosis of AD and FTD and symptoms onset before age 65 in the Modena province, Italy. By using regression models of cumulative occurrences, we also estimated age-specific prevalence and compared the growth curves of the clinical presentations.

RESULTS

The prevalence of all-variants AD increased with age, from 18/1,000,000 in the 40-44 age group to 1411/1,000,000 in the 60-64 age group. The prevalence of all-variants FTD also increased with age, from 18/1,000,000 to 866/1,000,000. An estimation of age-specific prevalence functions of each clinical presentation showed that atypical non-amnestic AD and aphasic FTD grew the most in early ages, followed by the behavioural variant of FTD (bvFTD). Then, around the age of 60, amnestic AD took over and its age-specific prevalence continued to increase disproportionally compared to all the other clinical variants of AD and FTD, which, instead, started to decrease in prevalence.

CONCLUSIONS

Amnestic AD is the clinical presentation that increases the most with advancing age, followed by bvFTD, suggesting that there is a differential vulnerability to the effect of ageing within the same neurodegenerative disease.

Greenness and neuropsychiatric symptoms in dementia

OBJECTIVES

It is acknowledged that living in a green environment may help mental well-being and this may be especially true for vulnerable people. However, the relationship between greenness and neuropsychiatric symptoms in dementia has not been explored yet.

METHODS

We collected clinical, neuropsychiatric, and residential data from subjects with dementia living in the province of Modena, Northern Italy. Neuropsychiatric symptoms were measured with the Neuropsychiatry Inventory, a questionnaire administered to the caregiver who assesses the presence and severity of neuropsychiatric symptoms, including delusions, hallucinations, agitation/aggression, dysphoria/depression, anxiety, euphoria/elation, apathy/indifference, disinhibition, irritability/lability, aberrant motor behaviors, sleep disturbances, and appetite/eating changes. Normalized Difference Vegetation Index (NDVI) was used as a proxy of greenness. Regression models were constructed to study the association between greenness and neuropsychiatric features.

RESULTS

155 patients with dementia were recruited. We found that greenness is variably associated with the risk of having neuropsychiatric symptoms. The risk of apathy was lower with lower levels of greenness (OR = 0.42, 95% CI 0.19-0.91 for NDVI below the median value). The risk of psychosis was higher with lower levels of greenness but with more imprecise values (OR = 1.77, 95% CI 0.84-3.73 for NDVI below the median value).

CONCLUSION

Our results suggest a possible association between greenness and neuropsychiatric symptoms in people with dementia. If replicated in larger samples, these findings will pave the road for identifying innovative greening strategies and interventions that can improve mental health in dementia.

Neuroanatomical Correlates of Cognitive Tests in Young-onset MCI

BACKGROUND

Mild Cognitive Impairment (MCI) is a heterogeneous condition characterised by cognitive changes that do not affect everyday functioning and may represent a predementia phase. Research on the neuroanatomical correlates of cognitive tests used to diagnose MCI is heterogeneous and has mainly focused on elderly populations of patients with MCI, usually well above the age of 65. However, the effect of ageing on brain structure is known to be substantial and to affect brain-behaviour associations in older people. We explored the brain correlates of different cognitive tests in a group of young-onset MCI (i.e., with symptoms onset before the age of 65) to minimise the effect of ageing on brain-behaviour associations.

METHODS

Patients with a clinical diagnosis of young-onset MCI underwent extensive cognitive assessment and multimodal Magnetic Resonance Imaging (MRI) including high-resolution T1-weighted and Diffusion Tensor Imaging (DTI) sequences. Their scores on cognitive tests were related to measures of grey matter (GM) density and white matter (WM) integrity using, respectively, Voxel Based Morphometry (VBM) and Tract-Based Spatial Statistics (TBSS).

RESULTS

104 young-onset MCI were recruited. VBM and TBSS whole-brain correlational analyses showed that between-subject variability in cognitive performance was significantly associated with regional variability in GM density and WM integrity. While associations between cognitive scores and focal GM density in our young-onset MCI group reflected the well-known lateralization of verbal and visuo-spatial abilities on the left and right hemispheres respectively, the associations between cognitive scores and WM microstructural integrity were widespread and diffusely involved most of the WM tracts in both hemispheres.

CONCLUSIONS

We investigated the structural neuroanatomical correlates of cognitive tests in young-onset MCI in order to minimise the effect of ageing on brain-behaviour associations.

The association between lifelong personality and clinical phenotype in the FTD-ALS spectrum

Introduction

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are two phenotypes of the same neurodegenerative disease, the FTD-ALS spectrum. What determines the development of one rather than the other phenotype is still unknown. Based on the clinical observation that patients' personality seems to differ between the two phenotypes, i.e., ALS patients tend to display kind, prosocial behaviors whereas FTD patients tend to present anti-social behaviors, and that these traits are often reported as pre-existing the disease onset by caregivers, we set up to study experimentally patients' personality in their premorbid life.

Methods

We first tested for differences between groups, then tested the association between premorbid personality and current functional organization of the brain. Premorbid personality of a cohort of forty patients, 27 FTD and 13 ALS, was explored through the NEO Personality Inventory 3 (NEO-PI-3), which analyses the five main personality factors, completed by the caregiver with reference to patient's personality 20 years before symptoms onset (premorbid). A subgroup of patients underwent a brain MRI including structural and resting-state functional MRI (rsfMRI).

Results

A significant difference between FTD and ALS in premorbid personality emerged in the Openness (133.92 FTD vs. 149.84 ALS, p = 0.01) and Extraversion (136.55 FTD vs. 150.53 ALS, p = 0.04) factors. This suggests that ALS patients had been, in their premorbid life, more open to new experiences, more sociable and optimistic than FTD patients. They also showed greater functional connectivity than both FTD and a control group in the Salience resting state network, over and above differences in gray matter atrophy. Finally, there was a positive correlation between premorbid Openness and functional connectivity in the Salience network across all patients, suggesting a possible association between premorbid personality and current functional organization of the brain, irrespective of the degree of atrophy.

Discussion

Our proof-of-concept results suggest that premorbid personality may eventually predispose to the development of one, rather than the other, phenotype in the FTD-ALS spectrum.

Multimodal nonlinear correlates of behavioural symptoms in frontotemporal dementia

Background

Studies exploring the brain correlates of behavioural symptoms in the frontotemporal dementia spectrum (FTD) have mainly searched for linear correlations with single modality neuroimaging data, either structural magnetic resonance imaging (MRI) or fluoro-deoxy-D-glucose positron emission tomography (FDG-PET). We aimed at studying the two imaging modalities in combination to identify nonlinear co-occurring patterns of atrophy and hypometabolism related to behavioural symptoms.

Methods

We analysed data from 93 FTD patients who underwent T1-weighted MRI, FDG-PET imaging, and neuropsychological assessment including the Neuropsychiatric Inventory, Frontal Systems Behaviour Scale, and Neurobehavioral Rating Scale. We used a data-driven approach to identify the principal components underlying behavioural variability, then related the identified components to brain variability using a newly developed method fusing maps of grey matter volume and FDG metabolism.

Results

A component representing apathy, executive dysfunction, and emotional withdrawal was associated with atrophy in bilateral anterior insula and putamen, and with hypometabolism in the right prefrontal cortex. Another component representing the disinhibition versus depression/mutism continuum was associated with atrophy in the right striatum and ventromedial prefrontal cortex for disinhibition, and hypometabolism in the left fronto-opercular region and sensorimotor cortices for depression/mutism. A component representing psychosis was associated with hypometabolism in the prefrontal cortex and hypermetabolism in auditory and visual cortices.

Discussion

Behavioural symptoms in FTD are associated with atrophy and altered metabolism of specific brain regions, especially located in the frontal lobes, in a hierarchical way: apathy and disinhibition are mostly associated with grey matter atrophy, whereas psychotic symptoms are mostly associated with hyper-/hypo-metabolism.

Automated detection of cerebral microbleeds on MR images using knowledge distillation framework

Introduction

Cerebral microbleeds (CMBs) are associated with white matter damage, and various neurodegenerative and cerebrovascular diseases. CMBs occur as small, circular hypointense lesions on T2*-weighted gradient recalled echo (GRE) and susceptibility-weighted imaging (SWI) images, and hyperintense on quantitative susceptibility mapping (QSM) images due to their paramagnetic nature. Accurate automated detection of CMBs would help to determine quantitative imaging biomarkers (e.g., CMB count) on large datasets. In this work, we propose a fully automated, deep learning-based, 3-step algorithm, using structural and anatomical properties of CMBs from any single input image modality (e.g., GRE/SWI/QSM) for their accurate detections.

Methods

In our method, the first step consists of an initial candidate detection step that detects CMBs with high sensitivity. In the second step, candidate discrimination step is performed using a knowledge distillation framework, with a multi-tasking teacher network that guides the student network to classify CMB and non-CMB instances in an offline manner. Finally, a morphological clean-up step further reduces false positives using anatomical constraints. We used four datasets consisting of different modalities specified above, acquired using various protocols and with a variety of pathological and demographic characteristics.

Results

On cross-validation within datasets, our method achieved a cluster-wise true positive rate (TPR) of over 90% with an average of <2 false positives per subject. The knowledge distillation framework improves the cluster-wise TPR of the student model by 15%. Our method is flexible in terms of the input modality and provides comparable cluster-wise TPR and better cluster-wise precision compared to existing state-of-the-art methods. When evaluating across different datasets, our method showed good generalizability with a cluster-wise TPR >80 % with different modalities. The python implementation of the proposed method is openly available.

Outdoor artificial light at night and risk of early-onset dementia: A case-control study in the Modena population, Northern Italy

Background

Dementia is a neurological syndrome characterized by severe cognitive impairment with functional impact on everyday life. It can be classified as young onset dementia (EOD) in case of symptom onset before 65, and late onset dementia (LOD). The purpose of this study is to assess the risk of dementia due to light pollution, and specifically outdoor artificial light at night (LAN).

Methods

Using a case-control design, we enrolled dementia patients newly-diagnosed in the province of Modena in the period 2017-2019 and a referent population from their caregivers. We geo-referenced the address of residence on the date of recruitment, provided it was stable for the previous five years. We assessed LAN exposure through 2015 nighttime luminance satellite images from the Visible Infrared Imaging Radiometer Suite (VIIRS). Using a logistic regression model adjusted for age, sex, and education, we calculated the risk of dementia associated with increasing LAN exposure, namely using <10 nW/cm²/sr as reference and considering ≥10-<40 nW/cm²/sr intermediate and ≥40 nW/cm²/sr high exposure, respectively We also implemented non-linear assessment using a spline regression model.

Results

We recruited 58 EOD cases, 34 LOD cases and 54 controls. Average LAN exposure levels overlapped for EOD cases and controls, while LOD cases showed higher levels. Compared with the lowest exposure, the risk of EOD associated with LAN was higher in the intermediate exposure (OR = 1.36, 95% CI 0.54-3.39), but not in the high exposure category (OR = 1.04, 95% CI 0.32-3.34). In contrast, the risk of LOD was positively associated with LAN exposure, with ORs of 2.58 (95% CI 0.26-25.97) and 3.50 (95% CI 0.32-38.87) in the intermediate and high exposure categories, respectively. The spline regression analysis showed substantial lack of association between LAN and EOD, while almost linear although highly imprecise association emerged for LOD.

Conclusions

Although the precision of the estimates was affected by the limited sample size and the study design did not allow us to exclude the presence of residual confounding, these results suggest a possible role of LAN in the etiology of dementia, particularly of its late-onset form.

The landscape of cognitive impairment in superoxide dismutase 1-amyotrophic lateral sclerosis

Although mutations in the superoxide dismutase 1 gene account for only a minority of total amyotrophic lateral sclerosis cases, the discovery of this gene has been crucial for amyotrophic lateral sclerosis research. Since the identification of superoxide dismutase 1 in 1993, the field of amyotrophic lateral sclerosis genetics has considerably widened, improving our understanding of the diverse pathogenic basis of amyotrophic lateral sclerosis. In this review, we focus on cognitive impairment in superoxide dismutase 1-amyotrophic lateral sclerosis patients. Literature has mostly reported that cognition remains intact in superoxide dismutase 1-amyotrophic lateral sclerosis patients, but recent reports highlight frontal lobe function frailty in patients carrying different superoxide dismutase 1-amyotrophic lateral sclerosis mutations. We thoroughly reviewed all the various mutations reported in the literature to contribute to a comprehensive database of superoxide dismutase 1-amyotrophic lateral sclerosis genotype-phenotype correlation. Such a resource could ultimately improve our mechanistic understanding of amyotrophic lateral sclerosis, enabling a more robust assessment of how the amyotrophic lateral sclerosis phenotype responds to different variants across genes, which is important for the therapeutic strategy targeting genetic mutations. Cognition in superoxide dismutase 1-amyotrophic lateral sclerosis deserves further longitudinal research since this peculiar frailty in patients with similar mutations can be conditioned by external factors, including environment and other unidentified agents including modifier genes.

Young Onset Alzheimer's Disease Associated with C9ORF72 Hexanucleotide Expansion: Further Evidence for a Still Unsolved Association

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are recognized as part of a disease continuum (FTD-ALS spectrum), in which the most common genetic cause is chromosome 9 open reading frame 72 (C9ORF72) gene hexanucleotide repeat expansion. The clinical phenotype of patients carrying this expansion varies widely and includes diseases beyond the FTD-ALS spectrum. Although a few cases of patients with C9ORF72 expansion and a clinical or biomarker-supported diagnosis of Alzheimer's disease (AD) have been described, they have been considered too sparse to establish a definite association between the C9ORF72 expansion and AD pathology. Here, we describe a C9ORF72 family with pleomorphic phenotypical expressions: a 54-year-old woman showing cognitive impairment and behavioral disturbances with both neuroimaging and cerebrospinal fluid (CSF) biomarkers consistent with AD pathology, her 49-year-old brother with typical FTD-ALS, and their 63-year-old mother with the behavioral variant of FTD and CSF biomarkers suggestive of AD pathology. The young onset of disease in all three family members and their different phenotypes and biomarker profiles make the simple co-occurrence of different diseases an extremely unlikely explanation. Our report adds to previous findings and may contribute to further expanding the spectrum of diseases associated with C9ORF72 expansion.

Vascular Collagen Type-IV in Hypertension and Cerebral Small Vessel Disease

BACKGROUND

Cerebral small vessel disease (SVD) is common in older people and causes lacunar stroke and vascular cognitive impairment. Risk factors include old age, hypertension and variants in the genes COL4A1/COL4A2 encoding collagen alpha-1(IV) and alpha-2(IV), here termed collagen-IV, which are core components of the basement membrane. We tested the hypothesis that increased vascular collagen-IV associates with clinical hypertension and with SVD in older persons and with chronic hypertension in young and aged primates and genetically hypertensive rats.

METHODS

We quantified vascular collagen-IV immunolabeling in small arteries in a cohort of older persons with minimal Alzheimer pathology (N=52; 21F/31M, age 82.8±6.95 years). We also studied archive tissue from young (age range 6.2-8.3 years) and older (17.0-22.7 years) primates (M mulatta) and compared chronically hypertensive animals (18 months aortic stenosis) with normotensives. We also compared genetically hypertensive and normotensive rats (aged 10-12 months).

RESULTS

Collagen-IV immunolabeling in cerebral small arteries of older persons was negatively associated with radiological SVD severity (ρ: -0.427, P=0.005) but was not related to history of hypertension. General linear models confirmed the negative association of lower collagen-IV with radiological SVD (P<0.017), including age as a covariate and either clinical hypertension (P<0.030) or neuropathological SVD diagnosis (P<0.022) as fixed factors. Reduced vascular collagen-IV was accompanied by accumulation of fibrillar collagens (types I and III) as indicated by immunogold electron microscopy. In young and aged primates, brain collagen-IV was elevated in older normotensive relative to young normotensive animals (P=0.029) but was not associated with hypertension. Genetically hypertensive rats did not differ from normotensive rats in terms of arterial collagen-IV.

CONCLUSIONS

Our cross-species data provide novel insight into sporadic SVD pathogenesis, supporting insufficient (rather than excessive) arterial collagen-IV in SVD, accompanied by matrix remodeling with elevated fibrillar collagen deposition. They also indicate that hypertension, a major risk factor for SVD, does not act by causing accumulation of brain vascular collagen-IV.

Selenoprotein P Concentrations in the Cerebrospinal Fluid and Serum of Individuals Affected by Amyotrophic Lateral Sclerosis, Mild Cognitive Impairment and Alzheimer’s Dementia

Selenoprotein P, a selenium-transporter protein, has been hypothesized to play a role in the etiology of neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and Alzheimer’s dementia (AD). However, data in humans are scarce and largely confined to autoptic samples. In this case–control study, we determined selenoprotein P concentrations in both the cerebrospinal fluid (CSF) and the serum of 50 individuals diagnosed with ALS, 30 with AD, 54 with mild cognitive impairment (MCI) and of 30 controls, using sandwich enzyme-linked immunosorbent assay (ELISA) methods. We found a positive and generally linear association between CSF and serum selenoprotein P concentrations in all groups. CSF selenoprotein P and biomarkers of neurodegeneration were positively associated in AD, while for MCI, we found an inverted-U-shaped relation. CSF selenoprotein P concentrations were higher in AD and MCI than in ALS and controls, while in serum, the highest concentrations were found in MCI and ALS. Logistic and cubic spline regression analyses showed an inverse association between CSF selenoprotein P levels and ALS risk, and a positive association for AD risk, while an inverted-U-shaped relation with MCI risk emerged. Conversely, serum selenoprotein P concentrations were positively associated with risk of all conditions but only in their lower range. Overall, these findings indicate some abnormalities of selenoprotein P concentrations in both the central nervous system and blood associated with ALS and neurocognitive disorders, though in different directions. These alterations may reflect either phenomena of etiologic relevance or disease-induced alterations of nutritional and metabolic status.

Predictive value of phospho-tau/total-tau ratio in amyloid-negative Mild Cognitive Impairment

BACKGROUND

In patients with Mild Cognitive Impairment and normal biomarkers of amyloid-β deposition, prognostication remains challenging.

METHODS

We aimed at identifying clinical features, patterns of brain atrophy, and risk of subsequent conversion to dementia in a clinical cohort of consecutive patients with Mild Cognitive Impairment and normal CSF amyloid-β_1-42 presenting to our Cognitive Neurology Clinic who were followed prospectively over an average of 25 months. We stratified them as Converters/Non-Converters to dementia based on clinical follow-up and compared baseline clinical features, CSF biomarkers, and pattern of atrophy on MRI data between groups.

RESULTS

Among 111 eligible patients (mean age 65,61 years; 56,8% were male), 41 patients developed a clinical diagnosis of dementia. Subjects with low baseline p/t-tau had twofold risk of future conversion compared to high p/t-tau ratio subjects (HR = 2.0, p = 0.026). When stratifying converters according to CSF p/t-tau ratio cut off value (0,17), those with values lower than the cut-off had significantly more MRI atrophy at baseline relative to Non-Converters in limbic structures.

CONCLUSION

In Mild Cognitive Impairment patients with negative CSF amyloid biomarker, CSF p/t-tau ratio may be useful to identify those at greater risk of subsequent conversion, possibly because of TDP43-related underlying pathology.

Eliciting Implicit Awareness in Alzheimer’s Disease and Mild Cognitive Impairment: A Task-Based Functional MRI Study

Background

Recent models of anosognosia in dementia have suggested the existence of an implicit component of self-awareness about one’s cognitive impairment that may remain preserved and continue to regulate behavioral, affective, and cognitive responses even in people who do not show an explicit awareness of their difficulties. Behavioral studies have used different strategies to demonstrate implicit awareness in patients with anosognosia, but no neuroimaging studies have yet investigated its neural bases.

Methods

Patients with amnestic mild cognitive impairment and dementia due to Alzheimer’s disease underwent functional magnetic resonance imaging (fMRI) during the execution of a color-naming task in which they were presented with neutral, negative, and dementia-related words (Dementia-Related Emotional Stroop).

Results

Twenty-one patients were recruited: 12 were classified as aware and 9 as unaware according to anosognosia scales (based on clinical judgment and patient-caregiver discrepancy). Behavioral results showed that aware patients took the longest time to process dementia-related words, although differences between word types were not significant, limiting interpretation of behavioral results. Imaging results showed that patients with preserved explicit awareness had a small positive differential activation of the posterior cingulate cortex (PCC) for the dementia-related words condition compared to the negative words, suggesting attribution of emotional valence to both conditions. PCC differential activation was instead negative in unaware patients, i.e., lower for dementia-related words relative to negative-words. In addition, the more negative the differential activation, the lower was the Stroop effect measuring implicit awareness.

Conclusion

Posterior cingulate cortex preserved response to dementia-related stimuli may be a marker of preserved implicit self-awareness.

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects

Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus, which are among the earliest and most frequent brain changes associated with Alzheimer disease (AD). However, CNNs typically achieve the highest accuracy on datasets acquired from the same domain as the training dataset. Transfer learning allows domain adaptation through further training on a limited dataset. In this study, we applied transfer learning on a network called spatial warping network segmentation (SWANS), developed and trained in a previous study. We used MR images of patients with clinical diagnoses of mild cognitive impairment (MCI) and AD, segmented by two different raters. By using transfer learning techniques, we developed four new models, using different training methods. Testing was performed using 26% of the original dataset, which was excluded from training as a hold‐out test set. In addition, 10% of the overall training dataset was used as a hold‐out validation set. Results showed that all the new models achieved better hippocampal segmentation quality than the baseline SWANS model (p_s < .001), with high similarity to the manual segmentations (mean dice [best model] = 0.878 ± 0.003). The best model was chosen based on visual assessment and volume percentage error (VPE). The increased precision in estimating hippocampal volumes allows the detection of small hippocampal abnormalities already present in the MCI phase (SD = [3.9 ± 0.6]%), which may be crucial for early diagnosis.

Automated Detection of Candidate Subjects With Cerebral Microbleeds Using Machine Learning

Cerebral microbleeds (CMBs) appear as small, circular, well defined hypointense lesions of a few mm in size on T2^*-weighted gradient recalled echo (T2^*-GRE) images and appear enhanced on susceptibility weighted images (SWI). Due to their small size, contrast variations and other mimics (e.g., blood vessels), CMBs are highly challenging to detect automatically. In large datasets (e.g., the UK Biobank dataset), exhaustively labelling CMBs manually is difficult and time consuming. Hence it would be useful to preselect candidate CMB subjects in order to focus on those for manual labelling, which is essential for training and testing automated CMB detection tools on these datasets. In this work, we aim to detect CMB candidate subjects from a larger dataset, UK Biobank, using a machine learning-based, computationally light pipeline. For our evaluation, we used 3 different datasets, with different intensity characteristics, acquired with different scanners. They include the UK Biobank dataset and two clinical datasets with different pathological conditions. We developed and evaluated our pipelines on different types of images, consisting of SWI or GRE images. We also used the UK Biobank dataset to compare our approach with alternative CMB preselection methods using non-imaging factors and/or imaging data. Finally, we evaluated the pipeline's generalisability across datasets. Our method provided subject-level detection accuracy > 80% on all the datasets (within-dataset results), and showed good generalisability across datasets, providing a consistent accuracy of over 80%, even when evaluated across different modalities.

Neurons derived from individual early Alzheimer's disease patients reflect their clinical vulnerability

Establishing preclinical models of Alzheimer's disease that predict clinical outcomes remains a critically important, yet to date not fully realized, goal. Models derived from human cells offer considerable advantages over non-human models, including the potential to reflect some of the inter-individual differences that are apparent in patients. Here we report an approach using induced pluripotent stem cell-derived cortical neurons from people with early symptomatic Alzheimer's disease where we sought a match between individual disease characteristics in the cells with analogous characteristics in the people from whom they were derived. We show that the response to amyloid-β burden in life, as measured by cognitive decline and brain activity levels, varies between individuals and this vulnerability rating correlates with the individual cellular vulnerability to extrinsic amyloid-β in vitro as measured by synapse loss and function. Our findings indicate that patient-induced pluripotent stem cell-derived cortical neurons not only present key aspects of Alzheimer's disease pathology but also reflect key aspects of the clinical phenotypes of the same patients. Cellular models that reflect an individual's in-life clinical vulnerability thus represent a tractable method of Alzheimer's disease modelling using clinical data in combination with cellular phenotypes.

Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images

Robust automated segmentation of white matter hyperintensities (WMHs) in different datasets (domains) is highly challenging due to differences in acquisition (scanner, sequence), population (WMH amount and location) and limited availability of manual segmentations to train supervised algorithms. In this work we explore various domain adaptation techniques such as transfer learning and domain adversarial learning methods, including domain adversarial neural networks and domain unlearning, to improve the generalisability of our recently proposed triplanar ensemble network, which is our baseline model. We used datasets with variations in intensity profile, lesion characteristics and acquired using different scanners. For the source domain, we considered a dataset consisting of data acquired from 3 different scanners, while the target domain consisted of 2 datasets. We evaluated the domain adaptation techniques on the target domain datasets, and additionally evaluated the performance on the source domain test dataset for the adversarial techniques. For transfer learning, we also studied various training options such as minimal number of unfrozen layers and subjects required for fine-tuning in the target domain. On comparing the performance of different techniques on the target dataset, domain adversarial training of neural network gave the best performance, making the technique promising for robust WMH segmentation.

Determinants of Caregiver Burden in Early-Onset Dementia

Introduction

Caregivers of patients with early-onset dementia (EOD) experience high levels of burden, which is known to be affected by caregivers' psychological features as well as by patients' and caregivers' demographical and social variables. Although potential clinical, demographical, and social determinants have been separately examined, it is not known how they reciprocally interact.

Methods

Ninety-two consecutive patient-caregiver dyads were recruited from the Cognitive Neurology Clinics of Modena, Northern Italy. Caregivers were asked to fill in questionnaires regarding their burden, psychological distress, and family economic status. Data were analyzed with multivariable regression models and then entered in a mediation model.

Results

Caregiver burden was positively related to female caregiver sex, spousal relationship to the patient, severity of patient's behavioral symptoms, diagnostic delay, and financial distress of the family. It was negatively related to disease duration, patient's education, region of birth, caregiver age, number of caregiver's days off work, number of offspring, and caregiver perception of patient's quality of life. While the effect of caregiver age, diagnostic delay, and of proxies of family or social network directly impacted on caregiver's burden, the effect of patient's disease duration, being a wife caregiver, financial distress, and number of caregiver's days off work was entirely mediated by the level of caregiver psychological distress.

Conclusions

Both direct actions (such as increasing social networks and shortening diagnostic delay) and indirect actions aimed at reducing psychological distress (such as increasing the number of caregiver's days off work and financial support) should be planned to reduce caregiver's burden.

Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images

White matter hyperintensities (WMHs) have been associated with various cerebrovascular and neurodegenerative diseases. Reliable quantification of WMHs is essential for understanding their clinical impact in normal and pathological populations. Automated segmentation of WMHs is highly challenging due to heterogeneity in WMH characteristics between deep and periventricular white matter, presence of artefacts and differences in the pathology and demographics of populations. In this work, we propose an ensemble triplanar network that combines the predictions from three different planes of brain MR images to provide an accurate WMH segmentation. In the loss functions the network uses anatomical information regarding WMH spatial distribution in loss functions, to improve the efficiency of segmentation and to overcome the contrast variations between deep and periventricular WMHs. We evaluated our method on 5 datasets, of which 3 are part of a publicly available dataset (training data for MICCAI WMH Segmentation Challenge 2017 - MWSC 2017) consisting of subjects from three different cohorts, and we also submitted our method to MWSC 2017 to be evaluated on the unseen test datasets. On evaluating our method separately in deep and periventricular regions, we observed robust and comparable performance in both regions. Our method performed better than most of the existing methods, including FSL BIANCA, and on par with the top ranking deep learning methods of MWSC 2017.

Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets

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We harmonised measures of WMHs across two studies on healthy ageing.

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Specific pre-processing strategies can increase comparability across studies.

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Modelling of biological differences is crucial to provide calibrated measures.

Large scale neuroimaging datasets present the possibility of providing normative distributions for a wide variety of neuroimaging markers, which would vastly improve the clinical utility of these measures. However, a major challenge is our current poor ability to integrate measures across different large-scale datasets, due to inconsistencies in imaging and non-imaging measures across the different protocols and populations. Here we explore the harmonisation of white matter hyperintensity (WMH) measures across two major studies of healthy elderly populations, the Whitehall II imaging sub-study and the UK Biobank. We identify pre-processing strategies that maximise the consistency across datasets and utilise multivariate regression to characterise study sample differences contributing to differences in WMH variations across studies. We also present a parser to harmonise WMH-relevant non-imaging variables across the two datasets. We show that we can provide highly calibrated WMH measures from these datasets with: (1) the inclusion of a number of specific standardised processing steps; and (2) appropriate modelling of sample differences through the alignment of demographic, cognitive and physiological variables. These results open up a wide range of applications for the study of WMHs and other neuroimaging markers across extensive databases of clinical data.

Splenial white matter integrity is associated with memory impairments in posterior cortical atrophy

Posterior cortical atrophy is an atypical form of Alzheimer’s disease characterized by visuospatial impairments and predominant tissue loss in the posterior parieto-occipital and temporo-occipital cortex. Whilst episodic memory is traditionally thought to be relatively preserved in posterior cortical atrophy, recent work indicates that memory impairments form a common clinical symptom in the early stages of the disease. Neuroimaging studies suggest that memory dysfunction in posterior cortical atrophy may originate from atrophy and functional hypoconnectivity of parietal cortex. The structural connectivity patterns underpinning these memory impairments, however, have not been investigated. This line of inquiry is of particular interest, as changes in white matter tracts of posterior cortical atrophy patients have been shown to be more extensive than expected based on posterior atrophy of grey matter. In this cross-sectional diffusion tensor imaging MRI study, we examine the relationship between white matter microstructure and verbal episodic memory in posterior cortical atrophy. We assessed episodic memory performance in a group of posterior cortical atrophy patients (n = 14) and a group of matched healthy control participants (n = 19) using the Free and Cued Selective Reminding Test with Immediate Recall. Diffusion tensor imaging measures were obtained for 13 of the posterior cortical atrophy patients and a second control group of 18 healthy adults. Patients and healthy controls demonstrated similar memory encoding performance, indicating that learning of verbal information was preserved in posterior cortical atrophy. However, retrieval of verbal items was significantly impaired in the patient group compared with control participants. As expected, tract-based spatial statistics analyses showed widespread reductions of white matter integrity in posterior cortical regions of patients compared with healthy adults. Correlation analyses indicated that poor verbal retrieval in the patient group was specifically associated with microstructural damage of the splenium of the corpus callosum. Post-hoc tractography analyses in healthy controls demonstrated that this splenial region was connected to thalamic radiations and the retrolenticular part of the internal capsule. These results provide insight into the brain circuits that underlie memory impairments in posterior cortical atrophy. From a cognitive perspective, we propose that the association between splenial integrity and memory dysfunction could arise indirectly via disruption of attentional processes. We discuss implications for the clinical phenotype and development of therapeutic aids for cognitive impairment in posterior cortical atrophy.

Anosognosia in Early- and Late-Onset Dementia and Its Association With Neuropsychiatric Symptoms

Background: The symptom anosognosia or unawareness of disease in dementia has mainly been studied in patients with late-onset dementia (LOD, ≥65 years), whereas little is known on whether it is also present in patients with early-onset dementia (EOD, <65 years). We aimed at investigating differences in anosognosia between LOD and EOD, by also studying its association with different clinical variants of EOD and the presence of neuropsychiatric symptoms. Methods: A total of 148 patients, 91 EOD and 57 LOD, were recruited and underwent extended clinical assessment and caregiver interview that included questionnaires aimed at measuring anosognosia and neuropsychiatric symptoms. Differences in anosognosia between EOD and LOD and between subgroups with different clinical variants were investigated, as well as correlation between anosognosia and neuropsychiatric symptoms. A regression analysis was applied to explore the association between anosognosia and development of neuropsychiatric symptoms during disease progression. Results: Median levels of anosognosia were not significantly different between EOD and LOD. Anosognosia increased overtime with disease progression and was higher in frontotemporal dementia patients or, more precisely, in frontotemporal dementia and Alzheimer's disease variants associated with involvement of the frontal lobes. Higher levels of early anosognosia were associated with higher frequency and severity of subsequent neuropsychiatric symptoms, in particular apathy, later in the course of the disease. Conclusion: Anosognosia is a frequent symptom of EOD, occurring in 94.5% of all-cause EOD, and it is associated with higher risk of developing neuropsychiatric symptoms during disease progression. Recognising anosognosia may be helpful for clinicians and families to reduce diagnostic delay and improve disease managment.

Dietary Habits and Risk of Early-Onset Dementia in an Italian Case-Control Study

Risk of early-onset dementia (EOD) might be modified by environmental factors and lifestyles, including diet. The aim of this study is to evaluate the association between dietary habits and EOD risk. We recruited 54 newly-diagnosed EOD patients in Modena (Northern Italy) and 54 caregivers as controls. We investigated dietary habits through a food frequency questionnaire, assessing both food intake and adherence to dietary patterns, namely the Greek-Mediterranean, the Dietary Approaches to Stop Hypertension (DASH), and the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diets. We modeled the relation between dietary factors and risk using the restricted cubic spline regression analysis. Cereal intake showed a U-shaped relation with EOD, with risk increasing above 350 g/day. A high intake (>400 g/day) of dairy products was also associated with excess risk. Although overall fish and seafood consumption showed no association with EOD risk, we found a U-shaped relation with preserved/tinned fish, and an inverse relation with other fish. Similarly, vegetables (especially leafy) showed a strong inverse association above 100 g/day, as did citrus and dry fruits. Overall, sweet consumption was not associated with EOD risk, while dry cake and ice-cream showed a positive relation and chocolate products an inverse one. For beverages, we found no relation with EOD risk apart from a U-shaped relation for coffee consumption. Concerning dietary patterns, EOD risk linearly decreased with the increasing adherence to the MIND pattern. On the other hand, an inverse association for the Greek-Mediterranean and DASH diets emerged only at very high adherence levels. To the best of our knowledge, this is the first study that explores the association between dietary factors and EOD risk, and suggests that adherence to the MIND dietary pattern may decrease such risk.

Detection of Alzheimer's Disease using cortical diffusion tensor imaging

The aim of this research was to test a novel in‐vivo brain MRI analysis method that could be used in clinical cohorts to investigate cortical architecture changes in patients with Alzheimer's Disease (AD). Three cohorts of patients with probable AD and healthy volunteers were used to assess the results of the method. The first group was used as the “Discovery” cohort, the second as the “Test” cohort and the last “ATN” (Amyloid, Tau, Neurodegeneration) cohort was used to test the method in an ADNI 3 cohort, comparing to amyloid and Tau PET. The method can detect altered quality of cortical grey matter in AD patients, providing an additional tool to assess AD, distinguishing between these and healthy controls with an accuracy range between good and excellent. These new measurements could be used within the “ATN” framework as an index of cortical microstructure quality and a marker of Neurodegeneration. Further development may aid diagnosis, patient selection, and quantification of the “Neurodegeneration” component in response to therapies in clinical trials.

Environmental Risk Factors for Early-Onset Alzheimer's Dementia and Frontotemporal Dementia: A Case-Control Study in Northern Italy

Background: Early-onset dementia (EOD) is defined as dementia with symptom onset before 65 years. The role of environmental risk factors in the etiology of EOD is still undefined. We aimed at assessing the role of environmental risk factors in EOD etiology, taking into account its different clinical types. Methods: Using a case-control study, we recruited all EOD cases referred to Modena hospitals from 2016 to 2019, while the referent population was drawn from cases' caregivers. We investigated residential history, occupational and environmental exposures to chemicals and lifestyle behaviors through a self-administered questionnaire. We computed the odds ratios of EOD risk (overall and restricting to the Alzheimer's dementia (AD) or frontotemporal dementia (FTD) diagnoses) and the corresponding 95% confidence intervals using an unconditional logistic regression model. Results: Fifty-eight EOD patients (19 FTD and 32 AD) and 54 controls agreed to participate. Most of the investigated exposures, such as occupational exposure to aluminum, pesticides, dyes, paints or thinners, were associated with an increased odds ratio (OR) for FTD but not for AD. Long-term use of selenium-containing dietary supplements was associated with increased OR for EOD and, particularly, for FTD. For both EOD forms, smoking and playing football showed an increased odds ratio, while cycling was associated with increased risk only in FTD. Overall sports practice appeared to be a protective factor for both types. Conclusions: Our results suggest a role of environmental and behavioral risk factors such as some chemical exposures and professional sports in EOD etiology, in particular with reference to FTD. Overall sports practice may be associated with a reduced EOD risk.

Life-style and occupational risk factors for early onset dementia in an Italian community

Background

Early onset dementia (EOD) is defined as dementia with symptoms onset before 65 years, deeply impacting on patients' employment and income, as well as on their families. Little is known about role of occupational and life-style risk factors, we aimed at assessing their role in disease etiology.

Methods

Using a case-control study design, we recruited all EOD cases resident in Modena province from October, 2016 to October, 2019, and a referent population drawn from patients' care-givers. We investigated residential, life-style history, and occupational and environmental exposures to toxics through a self-administered questionnaire. We used a multivariate unconditional logistic regression model adjusted for sex, age, and education to calculate odds ratios (ORs) and 95% confidence intervals (CIs) of EOD risk for exposed vs. non-exposed subjects.

Results

Overall, fifty-eight EOD cases and fifty-four controls agreed to participate. Possible life-style risk factors are to be widowed (10.3% of cases vs. 2% of controls), and to have a lower educational attainment. Also smoking (OR 1.3, 95% CI 0.6-2.9), playing football (OR 2.2, 95% CI 0.5-9.3) or cycling (OR 2.3, 95% CI 0.4-13.4) were associated with higher EOD risk, although overall sport practice appeared to be a powerful protective factor (OR 0.4, 95% CI 0.2-0.9), particularly swimming (OR 0.2, 95% CI 0.0-0.8). Among occupational factors, disease risk was associated with exposure to aluminum (OR 2.6, 95% CI 0.4-15.7), pesticides (OR 2.3, 95% CI 0.7-7.8), and dyes, paints or thinners (OR 1.7, 95% CI 0.6-5.0). Finally, disease risk was not associate to overall history of any trauma, while head trauma and especially upper arm trauma showed positive association.

Conclusions

Despite the study limitations, our results appear to support a role of modifiable risk factors in EOD etiology, particularly of some chemical exposures and professional sports, while overall sports practice may have a beneficial effect.

Key messages

Some modifiable environmental, occupational and life-style risk factors seem associated with EOD onset. Awareness of EOD environmental and occupational risk factors, as well as life-style ones, is advisable on a public health perspective.

Pancreaticoduodenectomy for paraduodenal pancreatitis is associated with a higher incidence of diabetes but a similar quality of life and pain control when compared to medical treatment

BACKGROUND

Paraduodenal pancreatitis is a focal form of chronic pancreatitis that affects the groove area between the duodenum and the head of the pancreas. Consensus regarding surgical or nonsurgical management as the best treatment option is still lacking.

METHODS

We retrospectively evaluated all patients managed for PP at The Pancreas Institute of the University Hospital Trust of Verona from 1990 to 2017. The outcomes of surgical vs. medical treatment with regard to pain control, quality of life and pancreatic insufficiency were evaluated through specific questionnaires.

RESULTS

The final study population consisted of 75 patients: 62.6% underwent surgery, and 37.4% were managed without surgery. All surgical procedures consisted of pancreaticoduodenectomy. The median follow-up from the diagnosis of paraduodenal pancreatitis was 60 (12-240) months. Patients who underwent surgery experienced a similar incidence of steatorrhea (44.7 vs. 52.6%; p = 0.4) but a significantly higher incidence of diabetes (59.6 vs. 10.7%; p < 0.01) when compared to those managed without surgery. There was no difference in terms of reported chronic pain (Graded Chronic Pain Scale, median 0 vs. 1; p = 0.1) and quality of life (Pancreatitis QoL Instrument, median 82 vs. 79; p = 0.2). However, surgical patients reported a worse level of self-care activities associated with glycemic control (Diabetes Self-Management Questionnaire, median 20 vs. 28, p = 0.02).

CONCLUSION

In patients affected by paraduodenal pancreatitis, surgery and medical therapy seem to obtain similar results in terms of quality of life and pain control. However, surgery is associated with an increased prevalence of postoperative diabetes with consequent relevant issues with self-care management. Surgery should be considered only in selected patients after adequate medical treatment.

Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding

White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factors and neurodegenerative diseases affect lesion load and spatial distribution. At the individual level, WMH vary in contrast, amount and distribution in different white matter regions. In this work, we aimed to improve BIANCA, the FSL tool for WMH segmentation, in order to better deal with these sources of variability. We worked on two stages of BIANCA by improving the lesion probability map estimation (classification stage) and making the lesion probability map thresholding stage automated and adaptive to local lesion probabilities. Firstly, in order to take into account the effect of population-level factors, we included population-level lesion probabilities, modelled with respect to a parametric factor (e.g. age), in the classification stage. Secondly, we tested BIANCA performance when using four alternative classifiers commonly used in the literature with respect to K-nearest neighbour algorithm (currently used for lesion probability map estimation in BIANCA). Finally, we propose LOCally Adaptive Threshold Estimation (LOCATE), a supervised method for determining optimal local thresholds to apply to the estimated lesion probability map, as an alternative option to global thresholding (i.e. applying the same threshold to the entire lesion probability map). For these experiments we used data from a neurodegenerative cohort, a vascular cohort and the cohorts available publicly as a part of a segmentation challenge. We observed that including population-level parametric lesion probabilities with respect to age and using alternative machine learning techniques provided negligible improvement. However, LOCATE provided a substantial improvement in the lesion segmentation performance, when compared to the global thresholding. It allowed to detect more deep lesions and provided better segmentation of periventricular lesion boundaries, despite the differences in the lesion spatial distribution and load across datasets. We further validated LOCATE on a cohort of CADASIL (Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy) patients, a genetic form of cerebral small vessel disease, and healthy controls, showing that LOCATE adapts well to wide variations in lesion load and spatial distribution.

Hippocampal network abnormalities explain amnesia after VGKCC-Ab related autoimmune limbic encephalitis

OBJECTIVE

Limbic encephalitis associated with antibodies to components of the voltage-gated potassium channel complex (VGKCC-Ab-LE) often leads to hippocampal atrophy and persistent memory impairment. Its long-term impact on regions beyond the hippocampus, and the relationship between brain damage and cognitive outcome, are poorly understood. We investigated the nature of structural and functional brain abnormalities following VGKCC-Ab-LE and its role in residual memory impairment.

METHOD

A cross-sectional group study was conducted. Twenty-four VGKCC-Ab-LE patients (20 male, 4 female; mean (SD) age 63.86 (11.31) years) were recruited post-acutely along with age- and sex-matched healthy controls for neuropsychological assessment, structural MRI and resting-state functional MRI (rs-fMRI). Structural abnormalities were determined using volumetry and voxel-based morphometry; rs-fMRI data were analysed to investigate hippocampal functional connectivity (FC). Associations of memory performance with neuroimaging measures were examined.

RESULTS

Patients showed selective memory impairment. Structural analyses revealed focal hippocampal atrophy within the medial temporal lobes, correlative atrophy in the mediodorsal thalamus, and additional volume reduction in the posteromedial cortex. There was no association between regional volumes and memory performance. Instead, patients demonstrated reduced posteromedial cortico-hippocampal and inter-hippocampal FC, which correlated with memory scores (r = 0.553; r = 0.582, respectively). The latter declined as a function of time since the acute illness (r = -0.531).

CONCLUSION

VGKCC-Ab-LE results in persistent isolated memory impairment. Patients have hippocampal atrophy with further reduced mediodorsal thalamic and posteromedial cortical volumes. Crucially, reduced FC of remaining hippocampal tissue correlates more closely with memory function than does regional atrophy.

Aβ42/Aβ40 and Aβ42/Aβ38 Ratios Are Associated with Measures of Gait Variability and Activities of Daily Living in Mild Alzheimer's Disease: A Pilot Study

Gait disturbances are some of the earliest changes in dementia and their monitoring presents an opportunity for early diagnosis. The exact relationship between gait and well-established biomarkers of Alzheimer’s disease (AD) remains to be clarified. In this study we compared gait-related measures with cerebrospinal fluid (CSF) markers of AD pathology. We recruited seventeen participants with mild AD in a multi-site study and performed gait assessment as well as lumbar punctures to obtain CSF. CSF Aβ₄₂/Aβ₄₀ and Aβ₄₂/Aβ₃₈ correlated positively with measures of variability (step time and step length) in the clinic-based assessments. This was driven by a negative relationship between gait variability and Aβ₄₀ and Aβ₃₈ but not Aβ₄₂.The amyloid ratios and gait variability measures were also associated with more severe functional impairment. We interpret these data as an indication that increasing amyloid production (i.e., increasing Aβ₄₀ and Aβ₃₈) is associated with diminishing cognitive-motor control of gait. These preliminary results suggest that the two amyloid ratios may be a marker of the earliest disturbances in the interplay between cognitive and motor control which characterize dementia.

Age-dependent association of white matter abnormality with cognition after TIA or minor stroke

OBJECTIVE

To investigate if the association between MRI-detectable white matter hyperintensity (WMH) and cognitive status reported in previous studies persists at older ages (>80 years), when some white matter abnormality is almost universally reported in clinical practice.

METHODS

Consecutive eligible patients from a population-based cohort of all TIA/nondisabling stroke (Oxford Vascular Study) underwent multimodal MRI, including fluid-attenuated inversion recovery and diffusion-weighted imaging, allowing automated measurement of WMH volume, mean diffusivity (MD), and fractional anisotropy (FA) in normal-appearing white matter using FSL tools. These measures were related to cognitive status (Montreal Cognitive Assessment) at age ≤80 vs >80 years.

RESULTS

Of 566 patients (mean [range] age 66.7 [20-102] years), 107 were aged >80 years. WMH volumes and MD/FA were strongly associated with cognitive status in patients aged ≤80 years (all p < 0.001 for WMH, MD, and FA) but not in patients aged >80 years (not significant for WMH, MD, and FA), with age interactions for WMH volume (p _interaction = 0.016) and MD (p _interaction = 0.037). Voxel-wise analyses also showed that lower Montreal Cognitive Assessment scores were associated with frontal WMH in patients ≤80 years, but not >80 years.

CONCLUSION

MRI markers of white matter damage are strongly related to cognition in patients with TIA/minor stroke at younger ages, but not at age >80 years. Clinicians and patients should not overinterpret the significance of these abnormalities at older ages.

Prognostic impact of Ki-67 proliferative index in resectable pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease characterized by complex biological features and poor prognosis. A prognostic stratification of PDAC would help to improve patient management. The aim of this study was to analyse the expression of Ki‐67 in relation to prognosis in a cohort of patients with PDAC who had surgical treatment.

Methods

Patients who had pancreatic resection between August 2010 and October 2014 for PDAC at two Italian centres were reviewed retrospectively. Patients with metastatic or locally advanced disease, those who received neoadjuvant chemotherapy, patients with PDAC arising from intraductal papillary mucinous neoplasm and those with missing data were excluded. Clinical and pathological data were retrieved and analysed. Ki‐67 expression was evaluated using immunohistochemistry and patients were stratified into three subgroups. Survival analyses were performed for disease‐free (DFS) and disease‐specific (DSS) survival outcomes according to Ki‐67 expression and tumour grading.

Results

A total of 170 patients met the selection criteria. Ki‐67 expression of 10 per cent or less, 11–50 per cent and more than 50 per cent significantly correlated with DFS and DSS outcomes (P = 0·016 and P = 0·002 respectively). Ki‐67 index was an independent predictor of poor DFS (hazard ratio (HR) 0·52, 95 per cent c.i. 0·29 to 0·91; P = 0·022) and DSS (HR 0·53, 0·31 to 0·91; P = 0·022). Moreover, Ki‐67 index correlated strongly with tumour grade (P < 0·001). Patients with PDAC classified as a G3 tumour with a Ki‐67 index above 50 per cent had poor survival outcomes compared with other patients (P < 0·001 for both DFS and DSS).

Conclusion

Ki‐67 index could be of use in predicting the survival of patients with PDAC. Further investigation in larger cohorts is needed to validate these results.

Selenium and selenium species in the etiology of Alzheimer's dementia: The potential for bias of the case-control study design

Several human studies imply that the trace element selenium and its species may influence the onset of neurological disease, including Alzheimer's dementia (AD). Nevertheless, the literature is conflicting, with reported associations between exposure and risk in opposite direction, possibly due to biases in exposure assessment. After conducting a cohort study that detected an excess AD risk associated with higher levels of inorganic-hexavalent selenium in subjects with mild cognitive impairment (MCI), we investigated the relation between selenium and AD using a case-control study design. We determined cerebrospinal fluid levels of selenium species in 56 MCI participants already included in the cohort study, considered as referents, and in 33 patients with established AD. AD risk was inversely correlated with inorganic selenium species and with the organic form bound to selenoprotein P. Selenium bound to other organo-selenium species was positively correlated with AD risk, suggesting compensatory selenoprotein upregulation following increased oxidative stress. The finding of an increased AD risk associated with inorganic-hexavalent selenium from the cohort study was not replicated. This case-control study yielded entirely different results than those generated by a cohort study with a partially overlapping participant population, suggesting that case-control design does not allow to reliably assess the role of selenium exposure in AD etiology. This inability appears to be due to exposure misclassification, falsely indicating an etiologic role of selenium deficiency likely due to reverse causation, and involving most selenium species. The case-control design may instead lend insights into the pathologic process underlying disease progression.

Attention network dysfunction underlies memory impairment in posterior cortical atrophy

Accumulating evidence suggests that memory is impaired in posterior cortical atrophy (PCA), alongside the early and defining visual disorder. The posterior parietal cortex is a key region of pathology in PCA and memory impairment may be the result of dysfunction of parietally dependent network function rather than the medial temporal lobe dependent dysfunction that defines the storage deficits in typical Alzheimer's disease. We assessed episodic memory performance and network function in16 PCA patients and 19 healthy controls who underwent structural and resting-state functional MRI and neuropsychological testing. Memory was assessed using the Free and Cued Selective Reminding Test (FCSRT), a sensitive test of episodic memory storage and retrieval. We examined correlations between memory performance and functional connectivity in the dorsal attention (DAN) and default mode network (DMN). Immediate recall on the FCSRT was relatively preserved in PCA patients. Total recall performance was impaired in patients relative to healthy controls and performance benefitted from retrieval cues. In patients only, disrupted connectivity in the DAN, but not the DMN, was associated with total recall. Memory impairment may arise from disruption to the dorsal attention network, subserved by the dorsal posterior parietal cortex, a key region of pathology in PCA, rather than classic medial temporal lobe memory circuitry.We propose that functional dysconnectivity in attentional circuits underpins memory impairment in PCA.

WP1-23 Vascular collagen 4A1 in subcortical white matter of older people and primates

Objectives

To test whether collagen 4A1 in cerebral small arteries associated with age, hypertension or small vessel disease (SVD).

Design

Neuropathology cohort study.

Subjects

Older people age >65 years with minimal Alzheimer’s Disease.

Methods

We examined subcortical white matter in archived brain tissue from older people (n=34, 15F/19M, median age 84, range 65–99 y) and from experimental non-human primates (NHP, Macaca mulatta) that were young adults (n=9, age 6.2–8.3 y) or older adults (n=8, age 17.0–22.7 y). Some of the primates (5 young, 3 older) were chronically hypertensive. Vascular collagen 4A1 immunohistochemical labelling was examined qualitatively and quantified as percent area fraction.

Results

Collagen 4A1 labelling was common in arterial myocytes and in the adventitial layer in human and primate brain arteries, as well as in basement membrane, which frequently exhibited replication. Among older people, collagen 4A1 associated with neuropathological SVD severity (sclerotic index; r=−0.461, p=0.0409, least squares) and with radiological SVD severity (leukoaraiosis; p=0.0455, 1-way ANOVA) but not with age or clinical history of hypertension. In NHP, age but not hypertension was significantly associated with collagen-4A1 labelling (p=0.0396, 0.232 respectively, 2-way ANOVA).

Conclusions

In this small cohort, vascular collagen 4A1 was related to SVD severity in older humans, in accord with genetic associations of COL4A1 with SVD phenotypes.

Longitudinal Brain Atrophy Rates in Transient Ischemic Attack and Minor Ischemic Stroke Patients and Cognitive Profiles

Introduction: Patients with transient ischemic attack (TIA) and minor stroke demonstrate cognitive impairment, and a four-fold risk of late-life dementia. Aim: To study the extent to which the rates of brain volume loss in TIA patients differ from healthy controls and how they are correlated with cognitive impairment. Methods: TIA or minor stroke patients were tested with a neuropsychological battery and underwent T1 weighted volumetric magnetic resonance imaging scans at fixed intervals over a 3 years period. Linear mixed effects regression models were used to compare brain atrophy rates between groups, and to determine the relationship between atrophy rates and cognitive function in TIA and minor stroke patients. Results: Whole brain atrophy rates were calculated for the TIA and minor stroke patients; n = 38 between 24 h and 18 months, and n = 68 participants between 18 and 36 months, and were compared to healthy controls. TIA and minor stroke patients demonstrated a significantly higher whole brain atrophy rate than healthy controls over a 3 years interval (p = 0.043). Diabetes (p = 0.012) independently predicted higher atrophy rate across groups. There was a relationship between higher rates of brain atrophy and processing speed (composite P = 0.047 and digit symbol coding P = 0.02), but there was no relationship with brain atrophy rates and memory or executive composite scores or individual cognitive tests for language (Boston naming, memory recall, verbal fluency or Trails A or B score). Conclusion: TIA and minor stroke patients experience a significantly higher rate of whole brain atrophy. In this cohort of TIA and minor stroke patients changes in brain volume over time precede cognitive decline.

Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference

White matter hyperintensities (WMH), also known as white matter lesions, are localised white matter areas that appear hyperintense on MRI scans. WMH commonly occur in the ageing population, and are often associated with several factors such as cognitive disorders, cardiovascular risk factors, cerebrovascular and neurodegenerative diseases. Despite the fact that some links between lesion location and parametric factors such as age have already been established, the relationship between voxel-wise spatial distribution of lesions and these factors is not yet well understood. Hence, it would be of clinical importance to model the distribution of lesions at the population-level and quantitatively analyse the effect of various factors on the lesion distribution model. In this work we compare various methods, including our proposed method, to generate voxel-wise distributions of WMH within a population with respect to various factors. Our proposed Bayesian spline method models the spatio-temporal distribution of WMH with respect to a parametric factor of interest, in this case age, within a population. Our probabilistic model takes as input the lesion segmentation binary maps of subjects belonging to various age groups and provides a population-level parametric lesion probability map as output. We used a spline representation to ensure a degree of smoothness in space and the dimension associated with the parameter, and formulated our model using a Bayesian framework. We tested our algorithm output on simulated data and compared our results with those obtained using various existing methods with different levels of algorithmic and computational complexity. We then compared the better performing methods on a real dataset, consisting of 1000 subjects of the UK Biobank, divided in two groups based on hypertension diagnosis. Finally, we applied our method on a clinical dataset of patients with vascular disease. On simulated dataset, the results from our algorithm showed a mean square error (MSE) value of 7.27×10-5, which was lower than the MSE value reported in the literature, with the advantage of being robust and computationally efficient. In the UK Biobank data, we found that the lesion probabilities are higher for the hypertension group compared to the non-hypertension group and further verified this finding using a statistical t-test. Finally, when applying our method on patients with vascular disease, we observed that the overall probability of lesions is significantly higher in later age groups, which is in line with the current literature.

Exploring variability in basal ganglia connectivity with functional MRI in healthy aging

Changes in functional connectivity (FC) measured using resting state fMRI within the basal ganglia network (BGN) have been observed in pathologies with altered neurotransmitter systems and conditions involving motor control and dopaminergic processes. However, less is known about non-disease factors affecting FC in the BGN. The aim of this study was to examine associations of FC within the BGN with dopaminergic processes in healthy older adults. We explored the relationship between FC in the BGN and variables related to demographics, impulsive behavior, self-paced tasks, mood, and motor correlates in 486 participants in the Whitehall-II imaging sub-study using both region-of-interest- and voxel-based approaches. Age was the only correlate of FC in the BGN that was consistently significant with both analyses. The observed adverse effect of aging on FC may relate to alterations of the dopaminergic system, but no unique dopamine-related function seemed to have a link with FC beyond those detectable in and linearly correlated with healthy aging.