Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy: A Bayesian Approach.

Background: Cognitive decline is a key outcome of clinical studies in Alzheimer's disease (AD). Objective: To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts. Methods: We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis. Results: We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases. Conclusions: We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid.

Cumulative mean fluorescent intensities of HLA specific antibodies predict antibody mediated rejections after kidney transplantation.

It is still not fully elucidated which pretransplant donor-specific HLA antibodies (DSA) are harmful after kidney transplantation. In particular, it needs to be clarified whether cumulative mean fluorescence intensities (MFI) against multiple HLA specificities have a predictive value for allograft function. Our retrospective single centre study analyzed preformed HLA antibodies determined by Luminex™ Single Antigen Bead (SAB) assay, including C1q addition, in relation to rejection and clinical outcome in 255 cross match negative kidney allograft recipients. Only 33 recipients (13%) of the total cohort showed early AMR during the first year posttransplant, but in patients with pre-transplant DSA the rate was increased to 15 out of 40 (38%). Three year graft survival was significantly shorter in patients with histological signs of AMR compared with patients without AMR or with no biopsy (74%, 92%, and 97%, respectively, p < 0.0001). In patients with HLA-DSA, a cumulative MFI value of all HLA antibodies of more than 103.000 indicated the highest risk for AMR posttransplant (p = 0.01). In conclusion, in patients with HLA-DSA, the cumulative MFI value may help to further stratify the risk of AMR after kidney transplantation.

Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer's disease.

BACKGROUND: Although convolutional neural networks (CNNs) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap as they allow the visualization of key input image features that drive the decision of the model. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge. METHODS: We trained a CNN for the detection of AD in N = 663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including in total N = 1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection. RESULTS: Across the three independent datasets, group separation showed high accuracy for AD dementia versus controls (AUC ≥ 0.91) and moderate accuracy for amnestic MCI versus controls (AUC ≈ 0.74). Relevance maps indicated that hippocampal atrophy was considered the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r ≈ -0.86, p < 0.001). CONCLUSION: The relevance maps highlighted atrophy in regions that we had hypothesized a priori. This strengthens the comprehensibility of the CNN models, which were trained in a purely data-driven manner based on the scans and diagnosis labels. The high hippocampus relevance scores as well as the high performance achieved in independent samples support the validity of the CNN models in the detection of AD-related MRI abnormalities. The presented data-driven and hypothesis-free CNN modeling approach might provide a useful tool to automatically derive discriminative features for complex diagnostic tasks where clear clinical criteria are still missing, for instance for the differential diagnosis between various types of dementia.

Pretransplant serum BAFF levels are associated with pretransplant HLA immunization and renal allograft survival.

BACKGROUND: The essential function of B cell-activating factor (BAFF) is regulating the survival and differentiation of B cells. The link between pretransplant BAFF levels and pretransplant alloimmunization and its value to predict subsequent acute antibody-mediated rejection (AMR) and outcome after renal transplantation is not fully understood. METHODS: Objective of our retrospective single-center study was to determine, by ELISA analysis of pretransplant serum BAFF levels in 249 patients undergoing renal transplantation, association between preformed anti-human leukocyte antigen (HLA) antibodies, occurrence of acute antibody mediated rejection (AMR) and renal allograft survival. RESULTS: Pretransplant serum BAFF levels were significantly higher in presensitized recipients with anti-HLA antibodies (3262±2796pg/ml) than in recipients without occurrence of anti-HLA antibodies (2252±1425pg/ml; p<0.0001). In addition, pretransplant BAFF levels correlated with cumulative MFI values of anti-HLA antibodies (r=0.2966, p=0.0025). Patients with high pretransplant BAFF levels (≥2137pg/ml) experienced significantly lower allograft survival rates compared to low pretransplant BAFF levels (80% vs. 91%; p=0.01). Coexistence of high pretransplant BAFF levels and posttransplant AMR was associated with the worst allograft survival rates (56%). Relative risk (RR) for allograft loss was associated with high serum BAFF levels (RR 2.3; p=0.02), presence of anti-HLA antibodies (RR 2.5; p=0.007) or anti-HLA -donor-specific antibodies (DSAs) (RR 2.6; p=0.003) before transplant and AMR post transplant (RR 2.5; p=0.007). AMR was the strongest independent risk factor for allograft failure (RR 2.6; p=0.03). CONCLUSION: Elevated pretransplant serum BAFF levels negatively affect renal allograft survival and represent a risk factor for allosensitization and subsequent AMR.