Cortical thickness modeling and variability in Alzheimer's disease and frontotemporal dementia

Alzheimer's disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC.We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14-3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity.We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability.We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.© 2023. The Author(s)

Classifying Alzheimer's disease and frontotemporal dementia using machine learning with cross-sectional and longitudinal magnetic resonance imaging data

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T-T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2-year follow-up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross-sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross-sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross-sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross-sectional and longitudinal data.© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC

Contribution of CSF biomarkers to early-onset Alzheimer's disease and frontotemporal dementia neuroimaging signatures

Prior studies have described distinct patterns of brain gray matter and white matter alterations in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), as well as differences in their cerebrospinal fluid (CSF) biomarkers profiles. We aim to investigate the relationship between early‐onset AD (EOAD) and FTLD structural alterations and CSF biomarker levels. We included 138 subjects (64 EOAD, 26 FTLD, and 48 controls), all of them with a 3T MRI brain scan and CSF biomarkers available (the 42 amino acid‐long form of the amyloid‐beta protein [Aβ42], total‐tau protein [T‐tau], neurofilament light chain [NfL], neurogranin [Ng], and 14‐3‐3 levels). We used FreeSurfer and FSL to obtain cortical thickness (CTh) and fraction anisotropy (FA) maps. We studied group differences in CTh and FA and described the “AD signature” and “FTLD signature.” We tested multiple regression models to find which CSF‐biomarkers better explained each disease neuroimaging signature. CTh and FA maps corresponding to the AD and FTLD signatures were in accordance with previous literature. Multiple regression analyses showed that the biomarkers that better explained CTh values within the AD signature were Aβ and 14‐3‐3; whereas NfL and 14‐3‐3 levels explained CTh values within the FTLD signature. Similarly, NfL levels explained FA values in the FTLD signature. Ng levels were not predictive in any of the models. Biochemical markers contribute differently to structural (CTh and FA) changes typical of AD and FTLD

Early and Late Peritoneal and Hepatic Changes in Goats Immunized with Recombinant Cathepsin L1 and Infected with Fasciola hepatica

The aim of the present study was to study peritoneal and hepatic changes during early [7-9 days postinfection (dpi)] and late [15 weeks postinfection (wpi)] infection of goats immunized with recombinant F. hepatica pro cathepsin L1 (rCL1) in Quil A and challenged with Fasciola hepatica. Despite finding no significant reduction in fluke burdens between the control and immunized group, at 15 dpi the rCL1-vaccinated group showed significantly higher weight gain and reduced severity of hepatic lesions compared with the control group that received only Quil A. In the rCL1-vaccinated group, two of three goats sacrificed at 7-9 dpi had little hepatic damage and had a higher percentage of peritoneal eosinophils and elevated induced nitric oxide synthase (iNOS) expression in peritoneal cells than the goats from the control group. Moreover, while these two goats showed a heavy infiltration of eosinophils surrounding migrating flukes, the remaining animals examined at 7-9 dpi had no inflammatory infiltration surrounding migrating flukes. Two out of seven goats in the rCL1-vaccinated group had low fluke burdens and little hepatic damage at 15 wpi, suggesting an effective protective response in some of the vaccinated goats. This protective response did not correlate with peripheral eosinophilia or with serum titres of anti-rCL1 immunoglobulin (Ig) G. The results of the present work suggest that an eosinophil-mediated immune response plays a crucial role in the early effective host response against F. hepatica in goats. Adjuvants designed to increase cell-mediated immunity should be tested in future vaccine trials against F. hepatica. © 2012 Elsevier Ltd

Early hepatic and peritoneal changes and immune response in goats vaccinated with a recombinant glutathione transferase sigma class and challenged with Fasciola hepatica.

Changes and local immune response were evaluated in the peritoneal cell populations, duodenal lamina propria and liver from goats immunized with recombinant glutathione transferase sigma class (rFhGST-S1) during early stages of infection with Fasciola hepatica. Group 1 (n=7) was unimmunized and uninfected; group 2 (n=10) was immunized with adjuvant Quil A and infected; group 3 (n=10) was immunised with rFhGST-S1 and infected. Three goats from each group were killed at 7-9 days post-infection (dpi) to evaluate early changes and immune response. The remaining goats were killed at 15 weeks post-infection (wpi). rFhGST-S1 vaccination induced variable response: three goats showed low fluke burden at 15 wpi and two goats showed low hepatic damage at early infection stages. This response was associated to a severe infiltrate of eosinophils in peritoneal fluid and hepatic necrotic foci, high iNOS expression in peritoneal cells and abundant infiltrate of eosinophils surrounding hepatic migrating flukes. T lymphocyte subsets were found in the vicinity of necrotic areas but they were absent in the vicinity of migrating larvae. No significant variation for T cell subsets, except for CD4 and γδ T lymphocytes, that were higher in the Quil A group compared to the rFhGST-S1 group. Expression of IL4 and IFN-γ in the hepatic inflammatory infiltrates was very occasional