| 1. |
- Abdelnour, Carla, et al.
(författare)
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Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data
- 2022
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Ingår i: Alzheimer's Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Dementia with Lewy bodies (DLB) includes various core clinical features that result in different phenotypes. In addition, Alzheimer's disease (AD) and cerebrovascular pathologies are common in DLB. All this increases the heterogeneity within DLB and hampers clinical diagnosis. We addressed this heterogeneity by investigating subgroups of patients with similar biological, clinical, and demographic features.Methods: We studied 107 extensively phenotyped DLB patients from the European DLB consortium. Factorial analysis of mixed data (FAMD) was used to identify dimensions in the data, based on sex, age, years of education, disease duration, Mini-Mental State Examination (MMSE), cerebrospinal fluid (CSF) levels of AD biomarkers, core features of DLB, and regional brain atrophy. Subsequently, hierarchical clustering analysis was used to subgroup individuals based on the FAMD dimensions.Results: We identified 3 dimensions using FAMD that explained 38% of the variance. Subsequent hierarchical clustering identified 4 clusters. Cluster 1 was characterized by amyloid-beta and cerebrovascular pathologies, medial temporal atrophy, and cognitive fluctuations. Cluster 2 had posterior atrophy and showed the lowest frequency of visual hallucinations and cognitive fluctuations and the worst cognitive performance. Cluster 3 had the highest frequency of tau pathology, showed posterior atrophy, and had a low frequency of parkinsonism. Cluster 4 had virtually normal AD biomarkers, the least regional brain atrophy and cerebrovascular pathology, and the highest MMSE scores.Conclusions: This study demonstrates that there are subgroups of DLB patients with different biological, clinical, and demographic characteristics. These findings may have implications in the diagnosis and prognosis of DLB, as well as in the treatment response in clinical trials.
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| 2. |
- af Winklerfelt Hammarberg, Sandra, et al.
(författare)
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Clinical effectiveness of care managers in collaborative primary health care for patients with depression : 12-and 24-month follow-up of a pragmatic cluster randomized controlled trial
- 2022
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Ingår i: BMC Primary Care. - : Springer Nature. - 2731-4553. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Background In previous studies, we investigated the effects of a care manager intervention for patients with depression treated in primary health care. At 6 months, care management improved depressive symptoms, remission, return to work, and adherence to anti-depressive medication more than care as usual. The aim of this study was to compare the long-term effectiveness of care management and usual care for primary care patients with depression on depressive symptoms, remission, quality of life, self-efficacy, confidence in care, and quality of care 12 and 24 months after the start of the intervention. Methods Cluster randomized controlled trial that included 23 primary care centers (11 intervention, 12 control) in the regions of Vastra Gotaland and Dalarna, Sweden. Patients >= 18 years with newly diagnosed mild to moderate depression (n = 376: 192 intervention, 184 control) were included. Patients at intervention centers co-developed a structured depression care plan with a care manager. Via 6 to 8 telephone contacts over 12 weeks, the care manager followed up symptoms and treatment, encouraged behavioral activation, provided education, and communicated with the patient's general practitioner as needed. Patients at control centers received usual care. Adjusted mixed model repeated measure analysis was conducted on data gathered at 12 and 24 months on depressive symptoms and remission (MADRS-S); quality of life (EQ5D); and self-efficacy, confidence in care, and quality of care (study-specific questionnaire). Results The intervention group had less severe depressive symptoms than the control group at 12 (P = 0.02) but not 24 months (P = 0.83). They reported higher quality of life at 12 (P = 0.01) but not 24 months (P = 0.88). Differences in remission and self-efficacy were not significant, but patients in the intervention group were more confident that they could get information (53% vs 38%; P = 0.02) and professional emotional support (51% vs 40%; P = 0.05) from the primary care center. Conclusions Patients with depression who had a care manager maintained their 6-month improvements in symptoms at the 12- and 24-month follow-ups. Without a care manager, recovery could take up to 24 months. Patients with care managers also had significantly more confidence in primary care and belief in future support than controls.
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| 3. |
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| 4. |
- Brusini, Irene
(författare)
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Methods for the analysis and characterization of brain morphology from MRI images
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Brain magnetic resonance imaging (MRI) is an imaging modality that produces detailed images of the brain without using any ionizing radiation. From a structural MRI scan, it is possible to extract morphological properties of different brain regions, such as their volume and shape. These measures can both allow a better understanding of how the brain changes due to multiple factors (e.g., environmental and pathological) and contribute to the identification of new imaging biomarkers of neurological and psychiatric diseases. The overall goal of the present thesis is to advance the knowledge on how brain MRI image processing can be effectively used to analyze and characterize brain structure.The first two works presented in this thesis are animal studies that primarily aim to use MRI data for analyzing differences between groups of interest. In Paper I, MRI scans from wild and domestic rabbits were processed to identify structural brain differences between these two groups. Domestication was found to significantly reshape brain structure in terms of both regional gray matter volume and white matter integrity. In Paper II, rat brain MRI scans were used to train a brain age prediction model. This model was then tested on both controls and a group of rats that underwent long-term environmental enrichment and dietary restriction. This healthy lifestyle intervention was shown to significantly affect the predicted brain age trajectories by slowing the rats' aging process compared to controls. Furthermore, brain age predicted on young adult rats was found to have a significant effect on survival.Papers III to V are human studies that propose deep learning-based methods for segmenting brain structures that can be severely affected by neurodegeneration. In particular, Papers III and IV focus on U-Net-based 2D segmentation of the corpus callosum (CC) in multiple sclerosis (MS) patients. In both studies, good segmentation accuracy was obtained and a significant correlation was found between CC area and the patient's level of cognitive and physical disability. Additionally, in Paper IV, shape analysis of the segmented CC revealed a significant association between disability and both CC thickness and bending angle. Conversely, in Paper V, a novel method for automatic segmentation of the hippocampus is proposed, which consists of embedding a statistical shape prior as context information into a U-Net-based framework. The inclusion of shape information was shown to significantly improve segmentation accuracy when testing the method on a new unseen cohort (i.e., different from the one used for training). Furthermore, good performance was observed across three different diagnostic groups (healthy controls, subjects with mild cognitive impairment and Alzheimer's patients) that were characterized by different levels of hippocampal atrophy.In summary, the studies presented in this thesis support the great value of MRI image analysis for the advancement of neuroscientific knowledge, and their contribution is mostly two-fold. First, by applying well-established processing methods on datasets that had not yet been explored in the literature, it was possible to characterize specific brain changes and disentangle relevant problems of a clinical or biological nature. Second, a technical contribution is provided by modifying and extending already-existing brain image processing methods to achieve good performance on new datasets.
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| 5. |
- Cedres, Nira, et al.
(författare)
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Association of Cerebrovascular and Alzheimer Disease Biomarkers With Cholinergic White Matter Degeneration in Cognitively Unimpaired Individuals
- 2022
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Ingår i: Neurology. - 0028-3878 .- 1526-632X. ; 99:15, s. e1619-e1629
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objectives Several pathologic processes might contribute to the degeneration of the cholinergic system in aging. We aimed to determine the contribution of amyloid, tau, and cerebrovascular biomarkers toward the degeneration of cholinergic white matter (WM) projections in cognitively unimpaired individuals.Methods The contribution of amyloid and tau pathology was assessed through CSF levels of the Aβ42/40 ratio and phosphorylated tau (p-tau). CSF Aβ38 levels were also measured. Cerebrovascular pathology was assessed using automatic segmentations of WM lesions (WMLs) on MRI. Cholinergic WM projections (i.e., cingulum and external capsule pathways) were modeled using tractography based on diffusion tensor imaging data. Sex and APOE ε4 carriership were also included in the analysis as variables of interest.Results We included 203 cognitively unimpaired individuals from the H70 Gothenburg Birth Cohort Studies (all individuals aged 70 years, 51% female). WM lesion burden was the most important contributor to the degeneration of both cholinergic pathways (increase in mean square error [IncMSE] = 98.8% in the external capsule pathway and IncMSE = 93.3% in the cingulum pathway). Levels of Aβ38 and p-tau also contributed to cholinergic WM degeneration, especially in the external capsule pathway (IncMSE = 28.4% and IncMSE = 23.4%, respectively). The Aβ42/40 ratio did not contribute notably to the models (IncMSE<3.0%). APOE ε4 carriers showed poorer integrity in the cingulum pathway (IncMSE = 21.33%). Women showed poorer integrity of the external capsule pathway (IncMSE = 21.55%), which was independent of amyloid status as reflected by the nonsignificant differences in integrity when comparing amyloid-positive vs amyloid-negative women participants (T201 = −1.55; p = 0.123).Discussion In cognitively unimpaired older individuals, WMLs play a central role in the degeneration of cholinergic pathways. Our findings highlight the importance of WM lesion burden in the elderly population, which should be considered in the development of prevention programs for neurodegeneration and cognitive impairment.
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| 6. |
- Dartora, Caroline, et al.
(författare)
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A deep learning model for brain age prediction using minimally preprocessed T1w images as input
- 2023
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Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (CNN)-based biological brain age prediction model that uses one T1w MRI preprocessing step when applying the model to external datasets to simplify implementation and increase accessibility in research settings. Our model only requires rigid image registration to the MNI space, which is an advantage compared to previous methods that require more preprocessing steps, such as feature extraction. Methods: We used a multicohort dataset of cognitively healthy individuals (age range = 32.0–95.7 years) comprising 17,296 MRIs for training and evaluation. We compared our model using hold-out (CNN1) and cross-validation (CNN2–4) approaches. To verify generalisability, we used two external datasets with different populations and MRI scan characteristics to evaluate the model. To demonstrate its usability, we included the external dataset’s images in the cross-validation training (CNN3). To ensure that our model used only the brain signal on the image, we also predicted brain age using skull-stripped images (CNN4). Results: The trained models achieved a mean absolute error of 2.99, 2.67, 2.67, and 3.08 years for CNN1–4, respectively. The model’s performance in the external dataset was in the typical range of mean absolute error (MAE) found in the literature for testing sets. Adding the external dataset to the training set (CNN3), overall, MAE is unaffected, but individual cohort MAE improves (5.63–2.25 years). Salience maps of predictions reveal that periventricular, temporal, and insular regions are the most important for age prediction. Discussion: We provide indicators for using biological (predicted) brain age as a metric for age correction in neuroimaging studies as an alternative to the traditional chronological age. In conclusion, using different approaches, our CNN-based model showed good performance using one T1w brain MRI preprocessing step. The proposed CNN model is made publicly available for the research community to be easily implemented and used to study ageing and age-related disorders.
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| 7. |
- Ekman, Urban, et al.
(författare)
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The MemClin project : a prospective multi memory clinics study targeting early stages of cognitive impairment
- 2020
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Ingår i: BMC Geriatrics. - : BMC. - 1471-2318. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Background: There remains a lack of large-scale clinical studies of cognitive impairment that aim to increase diagnostic and prognostic accuracy as well as validate previous research findings. The MemClin project will amass large quantities of cross-disciplinary data allowing for the construction of robust models to improve diagnostic accuracy, expand our knowledge on differential diagnostics, strengthen longitudinal prognosis, and harmonise examination protocols across centres. The current article describes the Memory Clinic (MemClin) project's study-design, materials and methods, and patient characteristics. In addition, we present preliminary descriptive data from the ongoing data collection.Methods: Nine out of ten memory clinics in the greater Stockholm area, which largely use the same examination methods, are included. The data collection of patients with different stages of cognitive impairment and dementia is coordinated centrally allowing for efficient and secure large-scale database construction. The MemClin project rest directly on the memory clinics examinations with cognitive measures, health parameters, and biomarkers.Results: Currently, the MemClin project has informed consent from 1543 patients. Herein, we present preliminary data from 835 patients with confirmed cognitive diagnosis and neuropsychological test data available. Of those, 239 had dementia, 487 mild cognitive impairment (MCI), and 104 subjective cognitive impairment (SCI). In addition, we present descriptive data on visual ratings of brain atrophy and cerebrospinal fluid markers.Conclusions: Based on our current progress and preliminary data, the MemClin project has a high potential to provide a large-scale database of 1200-1500 new patients annually. This coordinated data collection will allow for the construction of improved diagnostic and prognostic models for neurodegenerative disorders and other cognitive conditions in their naturalistic setting.
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| 8. |
- Elvsashagen, T, et al.
(författare)
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The genetic architecture of human brainstem structures and their involvement in common brain disorders
- 2020
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1, s. 4016-
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Tidskriftsartikel (refereegranskat)abstract
- Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders.
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| 9. |
- Gyllenhammar, Måns, et al.
(författare)
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The Association Between Temporal Atrophy and Episodic Memory Is Moderated by Education in a Multi-Center Memory Clinic Sample
- 2023
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Ingår i: Journal of Alzheimer's Disease. - 1387-2877 .- 1875-8908. ; 92:2, s. 605-614
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Tidskriftsartikel (refereegranskat)abstract
- Background: Cognitive reserve (CR) is hypothesized to partially explain the discrepancy between Alzheimer’s disease related brain pathology and cognitive performance. Educational attainment is often used as a proxy for CR.Objective: To examine the association of years of education and the relationship between atrophy in the medial temporal lobe and episodic memory, in a cross-sectional ecological multi-center memory clinic cohort.Methods: Included patients (n = 702) had undergone memory clinic examination and were diagnosed with subjective cognitive impairment (n = 99), mild cognitive impairment (n = 471), or dementia (n = 132). Total years of education were used as a moderating variable and neuropathology was operationalized as visual ratings of medial temporal lobe atrophy (MTA) on magnetic resonance imaging and computer tomography images. Weighted least squares regression and multiple regression were used to analyze moderation and the effect of education separately by diagnostic group. A composite score of two episodic memory tests constituted the dependent variable.Results: After controlling for age and gender the interaction term between MTA and years of education was significant indicating moderation. In particular, the regression model showed that at low levels of MTA, high education individuals had better episodic memory performance. However, at higher MTA levels, high education individuals had the lowest episodic memory performance. Education had a significant positive effect on episodic memory in SCI and MCI, but not dementia.Conclusion: These results extend the findings of education moderating the effect of MTA on cognition to a naturalistic memory clinic setting. Implications of the findings for theories on CR are discussed.
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| 10. |
- Janewithayapun, Ratchawit, 1998, et al.
(författare)
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Nanostructures of etherified arabinoxylans and the effect of arabinose content on material properties
- 2024
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Ingår i: Carbohydrate Polymers. - : Elsevier BV. - 0144-8617 .- 1879-1344. ; 331
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Tidskriftsartikel (refereegranskat)abstract
- To further our understanding of a thermoplastic arabinoxylan (AX) material obtained through an oxidation-reduction-etherification pathway, the role of the initial arabinose:xylose ratio on the material properties was investigated. Compression molded films with one molar substitution of butyl glycidyl ether (BGE) showed markedly different tensile behaviors. Films made from low arabinose AX were less ductile, while those made from high arabinose AX exhibited elastomer-like behaviors. X-ray scattering confirmed the presence of nanostructure formation resulting in nano-domains rich in either AX or BGE, from side chain grafting. The scattering data showed variations in the presence of ordered structures, nano-domain sizes and their temperature response between AX with different arabinose contents. In dynamic mechanical testing, three transitions were observed at approximately −90 °C, −50 °C and 80 °C, with a correlation between samples with more structured nano-domains and those with higher onset transition temperatures and lower storage modulus decrease. The mechanical properties of the final thermoplastic AX material can therefore be tuned by controlling the composition of the starting material.
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