Cerebrovascular disease in suspected non-Alzheimer's pathophysiology and cognitive decline over time.

BACKGROUND: The underlying cause of cognitive decline in individuals who are positive for biomarkers of neurodegeneration (N) but negative for biomarkers of amyloid-beta (A), designated as Suspected non-Alzheimer's pathophysiology (SNAP), remains unclear. We evaluate whether cerebrovascular disease (CeVD) is more prevalent in those with SNAP compared to A-N- and A+N+ individuals and whether CeVD is associated with cognitive decline over time in SNAP patients. METHODS: A total of 216 individuals from a prospective memory clinic cohort (mean [SD] age, 72.7 [7.3] years, 100 women [56.5%]) were included and were diagnosed as no cognitive impairment (NCI), cognitive impairment no dementia (CIND), Alzheimer's dementia (AD) or vascular dementia (VaD). All individuals underwent clinical evaluation and neuropsychological assessment annually for up to 5 years. Carbon 11-labeled Pittsburgh Compound B ([11 C]-PiB) or [18 F]-flutafuranol-positron emission spectrometry imaging was performed to ascertain amyloid-beta status. Magnetic resonance imaging was performed to assess neurodegeneration as measured by medial temporal atrophy ≥2, as well as significant CeVD (sCeVD) burden, defined by cortical infarct count ≥1, Fazekas score ≥2, lacune count ≥2 or cerebral microbleed count ≥2. RESULTS: Of the 216 individuals, 50 (23.1%) A-N+ were (SNAP), 93 (43.1%) A-N-, 36 (16.7%) A+N- and 37 (17.1%) A+N+. A+N+ individuals were significantly older, while A+N+ and SNAP individuals were more likely to have dementia. The SNAP group had a higher prevalence of sCeVD (90.0%) compared to A-N-. Moreover, SNAP individuals with sCeVD had significantly steeper decline in global cognition compared to A-N- over 5 years (p = 0.042). CONCLUSIONS: These findings suggest that CeVD is a contributing factor to cognitive decline in SNAP. Therefore, SNAP individuals should be carefully assessed and treated for CeVD.

Improved amyloid burden quantification with nonspecific estimates using deep learning.

PURPOSE: Standardized uptake value ratio (SUVr) used to quantify amyloid-ß burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we propose a novel amyloid-PET quantification approach that harnesses the intermodal image translation capability of convolutional networks to remove this undesirable source of variability. METHODS: Paired MR and PET images exhibiting very low specific uptake were selected from a Singaporean amyloid-PET study involving 172 participants with different severities of CeVD. Two convolutional neural networks (CNN), ScaleNet and HighRes3DNet, and one conditional generative adversarial network (cGAN) were trained to map structural MR to NS PET images. NS estimates generated for all subjects using the most promising network were then subtracted from SUVr images to determine specific amyloid load only (SAßL). Associations of SAßL with various cognitive and functional test scores were then computed and compared to results using conventional SUVr. RESULTS: Multimodal ScaleNet outperformed other networks in predicting the NS content in cortical gray matter with a mean relative error below 2%. Compared to SUVr, SAßL showed increased association with cognitive and functional test scores by up to 67%. CONCLUSION: Removing the undesirable NS uptake from the amyloid load measurement is possible using deep learning and substantially improves its accuracy. This novel analysis approach opens a new window of opportunity for improved data modeling in Alzheimer's disease and for other neurodegenerative diseases that utilize PET imaging.

Head-to-head comparison of amplified plasmonic exosome Aß42 platform and single-molecule array immunoassay in a memory clinic cohort.

BACKGROUND AND PURPOSE: Various blood biomarkers reflecting brain amyloid-ß (Aß) load have recently been proposed with promising results. However, to date, no comparative study amongst blood biomarkers has been reported. Our objective was to examine the diagnostic performance and cost effectiveness of three blood biomarkers on the same cohort. METHODS: Using the same cohort (n = 68), the performances of the single-molecule array (Simoa) Aß40, Aß42, Aß42/Aß40 and the amplified plasmonic exosome (APEX) Aß42 blood biomarkers were compared using amyloid positron emission tomography (PET) as the reference standard. The extent to which these blood tests can reduce the recruitment cost of clinical trials was also determined by identifying amyloid positive (Aß+) participants. RESULTS: Compared to Simoa biomarkers, APEX-Aß42 showed significantly higher correlations with amyloid PET retention values and excellent diagnostic performance (sensitivity 100%, specificity 93.3%, area under the curve 0.995). When utilized for clinical trial recruitment, our simulation showed that pre-screening with blood biomarkers followed by a confirmatory amyloid PET imaging would roughly half the cost (56.8% reduction for APEX-Aß42 and 48.6% for Simoa-Aß42/Aß40) compared to the situation where only PET imaging is used. Moreover, with 100% sensitivity, APEX-Aß42 pre-screening does not increase the required number of initial participants. CONCLUSIONS: With its high diagnostic performance, APEX is an ideal candidate for Aß+ subject identification, monitoring and primary care screening, and could efficiently enrich clinical trials with Aß+ participants whilst halving recruitment costs.

Plasma P-tau181 to Aß42 ratio is associated with brain amyloid burden and hippocampal atrophy in an Asian cohort of Alzheimer's disease patients with concomitant cerebrovascular disease.

INTRODUCTION: There is increasing evidence that phosphorylated tau (P-tau181) is a specific biomarker for Alzheimer's disease (AD) pathology, but its potential utility in non-White patient cohorts and patients with concomitant cerebrovascular disease (CeVD) is unknown. METHODS: Single molecule array (Simoa) measurements of plasma P-tau181, total tau, amyloid beta (Aß)40 and Aß42, as well as derived ratios were correlated with neuroimaging modalities indicating brain amyloid (Aß+), hippocampal atrophy, and CeVD in a Singapore-based cohort of non-cognitively impaired (NCI; n = 43), cognitively impaired no dementia (CIND; n = 91), AD (n = 44), and vascular dementia (VaD; n = 22) subjects. RESULTS: P-tau181/Aß42 ratio showed the highest area under the curve (AUC) for Aß+ (AUC = 0.889) and for discriminating between AD Aß+ and VaD Aß- subjects (AUC = 0.903). In addition, P-tau181/Aß42 ratio was associated with hippocampal atrophy. None of the biomarkers was associated with CeVD. DISCUSSION: Plasma P-tau181/Aß42 ratio may be a noninvasive means of identifying AD with elevated brain amyloid in populations with concomitant CeVD.

Improved quantification of amyloid burden and associated biomarker cut-off points: results from the first amyloid Singaporean cohort with overlapping cerebrovascular disease.

PURPOSE: The analysis of the [11C]PiB-PET amyloid images of a unique Asian cohort of 186 participants featuring overlapping vascular diseases raised the question about the validity of current standards for amyloid quantification under abnormal conditions. In this work, we implemented a novel pipeline for improved amyloid PET quantification of this atypical cohort. METHODS: The investigated data correction and amyloid quantification methods included motion correction, standardized uptake value ratio (SUVr) quantification using the parcellated MRI (standard method) and SUVr quantification without MRI. We introduced a novel amyloid analysis method yielding 2 biomarkers: AßL which quantifies the global Aß burden and ns that characterizes the non-specific uptake. Cut-off points were first determined using visual assessment as ground truth and then using unsupervised classification techniques. RESULTS: Subject's motion impacts the accuracy of the measurement outcome but has however a limited effect on the visual rating and cut-off point determination. SUVr computation can be reliably performed for all the subjects without MRI parcellation while, when required, the parcellation failed or was of mediocre quality in 10% of the cases. The novel biomarker AßL showed an association increase of 29.5% with the cognitive tests and increased effect size between positive and negative scans compared with SUVr. ns was found sensitive to cerebral microbleeds, white matter hyperintensity, volume, and age. The cut-off points for SUVr using parcellated MRI, SUVr without parcellation, and AßL were 1.56, 1.39, and 25.5. Finally, k-means produced valid cut-off points without the requirement of visual assessment. CONCLUSION: The optimal processing for the amyloid quantification of this atypical cohort allows the quantification of all the subjects, producing SUVr values and two novel biomarkers: AßL, showing important increased in their association with various cognitive tests, and ns, a parameter sensitive to non-specific retention variations caused by age and cerebrovascular diseases.

Somatic inactivation of E-cadherin and p53 in mice leads to metastatic lobular mammary carcinoma through induction of anoikis resistance and angiogenesis.

Metastatic disease is the primary cause of death in breast cancer, the most common malignancy in Western women. Loss of E-cadherin is associated with tumor metastasis, as well as with invasive lobular carcinoma (ILC), which accounts for 10%-15% of all breast cancers. To study the role of E-cadherin in breast oncogenesis, we have introduced conditional E-cadherin mutations into a mouse tumor model based on epithelium-specific knockout of p53. Combined loss of E-cadherin and p53 resulted in accelerated development of invasive and metastatic mammary carcinomas, which show strong resemblance to human ILC. Moreover, loss of E-cadherin induced anoikis resistance and facilitated angiogenesis, thus promoting metastatic disease. Our results suggest that loss of E-cadherin contributes to both mammary tumor initiation and metastasis.

The Association Between Standard Electrocardiography and Cerebral Small Vessel Disease in a Memory Clinic Study.

BACKGROUND: P-wave terminal force in lead V1 (PTFV1) on electrocardiography has been associated with atrial fibrillation and ischemic stroke. OBJECTIVE: To investigate whether PTFV1 is associated with cerebral small vessel disease (CSVD) markers and etiological subtypes of cognitive impairment and dementia. METHODS: Participants were recruited from ongoing memory clinic study between August 2010 to January 2019. All participants underwent physical and medical evaluation along with an electrocardiography and 3 T brain magnetic resonance imaging. Participants were classified as no cognitive impairment, cognitive impairment no dementia, vascular cognitive impairment no dementia, and dementia subtypes (Alzheimer's disease and vascular dementia). Elevated PTFV1 was defined as > 4,000µV×ms and measured manually on ECG. RESULTS: Of 408 participants, 78 (19.1%) had elevated PTFV1 (37 women [47%]; mean [SD] age, 73.8 [7.2] years). The participants with elevated PTFV1 had higher burden of lacunes, cerebral microbleeds (CMB), and cortical microinfarcts. As for the CMB location, persons with strictly deep CMB and mixed CMB had significantly higher PTFV1 than those with no CMB (p = 0.005, p = 0.007). Regardless of adjustment for cardiovascular risk factors and/or heart diseases, elevated PTFV1 was significantly associated with presence of CMB (odds ratio, 2.26; 95% CI,1.33-3.91). CONCLUSION: Elevated PTFV1 was associated with CSVD, especially deep CMB. PTFV1 in vascular dementia was also higher compared to Alzheimer's disease. Thus, PTFV1 might be a potential surrogate marker of brain-heart connection and vascular brain damage.

Brain amyloid ß, cerebral small vessel disease, and cognition: A memory clinic study.

OBJECTIVE: To evaluate the association between brain amyloid ß (Aß) and cerebral small vessel disease (CSVD) markers, as well as their joint effect on cognition, in a memory clinic study. METHODS: A total of 186 individuals visiting a memory clinic, diagnosed with no cognitive impairment, cognitive impairment no dementia (CIND), Alzheimer dementia (AD), or vascular dementia were included. Brain Aß was measured by [11C] Pittsburgh compound B-PET global standardized uptake value ratio (SUVR). CSVD markers including white matter hyperintensities (WMH), lacunes, and cerebral microbleeds (CMBs) were graded on MRI. Cognition was assessed by neuropsychological testing. RESULTS: An increase in global SUVR is associated with a decrease in Mini-Mental State Examination (MMSE) in CIND and AD, as well as a decrease in global cognition Z score in AD, independent of age, education, hippocampal volume, and markers of CSVD. A significant interaction between global SUVR and WMH was found in relation to MMSE in CIND (P for interaction: 0.009), with an increase of the effect size of Aß (ß = -6.57 [-9.62 to -3.54], p < 0.001) compared to the model without the interaction term (ß = -2.91 [-4.54 to -1.29], p = 0.001). CONCLUSION: Higher global SUVR was associated with worse cognition in CIND and AD, but was augmented by an interaction between global SUVR and WMH only in CIND. This suggests that Aß and CSVD are independent processes with a possible synergistic effect between Aß and WMH in individuals with CIND. There was no interaction effect between Aß and lacunes or CMBs. Therefore, in preclinical phases of AD, WMH should be targeted as a potentially modifiable factor to prevent worsening of cognitive dysfunction.

Prediction of poor clinical outcome in vascular cognitive impairment: TRACE-VCI study.

INTRODUCTION: Prognostication in memory clinic patients with vascular brain injury (eg possible vascular cognitive impairment [VCI]) is often uncertain. We created a risk score to predict poor clinical outcome. METHODS: Using data from two longitudinal cohorts of memory clinic patients with vascular brain injury without advanced dementia, we created (n = 707) and validated (n = 235) the risk score. Poor clinical outcome was defined as substantial cognitive decline (change of Clinical Dementia Rating ≥1 or institutionalization) or major vascular events or death. Twenty-four candidate predictors were evaluated using Cox proportional hazard models. RESULTS: Age, clinical syndrome diagnosis, Disability Assessment for Dementia, Neuropsychiatric Inventory, and medial temporal lobe atrophy most strongly predicted poor outcome and constituted the risk score (C-statistic 0.71; validation cohort 0.78). Of note, none of the vascular predictors were retained in this model. The 2-year risk of poor outcome was 6.5% for the lowest (0-5) and 55.4% for the highest sum scores (10-13). DISCUSSION: This is the first, validated, prediction score for 2-year clinical outcome of patients with possible VCI.