| 1. |
|
|
| 2. |
|
|
| 3. |
- Abdelnour, Carla, et al.
(författare)
-
Parsing heterogeneity within dementia with Lewy bodies using clustering of biological, clinical, and demographic data
- 2022
-
Ingår i: Alzheimer's Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 14:1
-
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.
|
|
| 4. |
- Albrecht, Franziska, et al.
(författare)
-
Effects of a Highly Challenging Balance Training Program on Motor Function and Brain Structure in Parkinson's Disease
- 2021
-
Ingår i: Journal of Parkinson's Disease. - : IOS Press. - 1877-7171 .- 1877-718X. ; 11:4, s. 2057-2071
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Parkinson's disease (PD) is characterized by motor deficits and brain alterations having a detrimental impact on balance, gait, and cognition. Intensive physical exercise can induce changes in the neural system, potentially counteracting neurodegeneration in PD and improving clinical symptoms. Objective: This randomized controlled trial investigated effects of a highly challenging, cognitively demanding, balance and gait training (HiBalance) program in participants with PD on brain structure. Methods: 95 participants were assigned to either the HiBalance or an active control speech training program. The group-based interventions were performed in 1-hour sessions, twice per week over a 10-week period. Participants underwent balance, gait, cognitive function, and structural magnetic resonance imaging assessments before and after the interventions. Voxel-based morphometry was analyzed in 34 HiBalance and 31 active controls. Additionally, structural covariance networks were assessed. Results: There was no significant time by group interaction between the HiBalance and control training in balance, gait, or brain volume. Within-HiBalance-group analyses showed higher left putamen volumes post-training. In repeated measures correlation a positive linear, non-significant relationship between gait speed and putamen volume was revealed. In the HiBalance group we found community structure changes and stronger thalamic-cerebellar connectivity in structural covariance networks. Neither brain volume changes nor topology changes were found for the active controls after the training. Conclusion: Thus, subtle structural brain changes occur after balance and gait training. Future studies need to determine whether training modifications or other assessment methods lead to stronger effects.
|
|
| 5. |
- Anderson, Ryan T, et al.
(författare)
-
Association Between Seroclearance of Hepatitis B Surface Antigen and Long-term Clinical Outcomes of Patients With Chronic Hepatitis B Virus Infection : Systematic Review and Meta-analysis.
- 2021
-
Ingår i: Clinical Gastroenterology and Hepatology. - : Elsevier. - 1542-3565 .- 1542-7714. ; 19:3, s. 463-472
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND & AIMS: Seroclearance of hepatitis B surface antigen (HBsAg) is the desired end point of treatment for chronic hepatitis B virus (HBV) infection, according to guidelines. We performed a systematic review and meta-analysis to evaluate the strength of the association between HBsAg seroclearance and long-term clinical outcomes.METHODS: We performed a systematic review of the PubMed, EMBASE, and Cochrane Library databases for articles that assessed HBsAg status and reported the incidence of hepatocellular carcinoma (HCC), liver decompensation, liver transplantation, and/or all-cause mortality during follow-up evaluation. We performed a meta-analysis of rate ratios (RR) using a random-effects model independently for each end point and for a composite end point.RESULTS: We analyzed data from 28 studies, comprising a total of 188,316 patients with chronic HBV infection (treated and untreated), and 1,486,081 person-years (PY) of follow-up evaluation; 26 reported data on HCC, 7 on liver decompensation, and 13 on liver transplantation and/or death. The composite event rates were 0.19/1000 PY for the HBsAg seroclearance group and 2.45/1000 PY for the HBsAg-persistent group. Pooled RRs for the HBsAg seroclearance group were 0.28 for liver decompensation (95% CI, 0.13-0.59; P = .001), 0.30 for HCC (95% CI, 0.20-0.44; P < .001), 0.22 for liver transplantation and/or death (95% CI, 0.13-0.39; P < .001), and 0.31 for the composite end point (95% CI, 0.23-0.43; P < .001). No differences in RR estimates were observed among subgroups of different study or patient characteristics.CONCLUSIONS: In a systematic review and meta-analysis, we found seroclearance of HBsAg to be associated significantly with improved patient outcomes. The results are consistent among different types of studies, in all patient subpopulations examined, and support the use of HBsAg seroclearance as a primary end point of trials of patients with chronic HBV infection.
|
|
| 6. |
- Borda, Miguel German, et al.
(författare)
-
Using magnetic resonance imaging to measure head muscles: An innovative method to opportunistically determine muscle mass and detect sarcopenia
- 2023
-
Ingår i: Journal of Cachexia, Sarcopenia and Muscle. - 2190-5991 .- 2190-6009.
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Sarcopenia is associated with multiple adverse outcomes. Traditional methods to determine low muscle mass for the diagnosis of sarcopenia are mainly based on dual-energy X-ray absorptiometry (DXA), whole-body magnetic resonance imaging (MRI) and bioelectrical impedance analysis. These tests are not always available and are rather time consuming and expensive. However, many brain and head diseases require a head MRI. In this study, we aim to provide a more accessible way to detect sarcopenia by comparing the traditional method of DXA lean mass estimation versus the tongue and masseter muscle mass assessed in a standard brain MRI. Methods: The H70 study is a longitudinal study of older people living in Gothenburg, Sweden. In this cross-sectional analysis, from 1203 participants aged 70 years at baseline, we included 495 with clinical data and MRI images available. We used the appendicular lean soft tissue index (ALSTI) in DXA images as our reference measure of lean mass. Images from the masseter and tongue were analysed and segmented using 3D Slicer. For the statistical analysis, the Spearman correlation coefficient was used, and concordance was estimated with the Kappa coefficient. Results: The final sample consisted of 495 participants, of which 52.3% were females. We found a significant correlation coefficient between both tongue (0.26) and masseter (0.33) with ALSTI (P < 0.001). The sarcopenia prevalence confirmed using the alternative muscle measure in MRI was calculated using the ALSTI (tongue = 2.0%, masseter = 2.2%, ALSTI = 2.4%). Concordance between sarcopenia with masseter and tongue versus sarcopenia with ALSTI as reference has a Kappa of 0.989 (P < 0.001) for masseter and a Kappa of 1 for the tongue muscle (P < 0.001). Comorbidities evaluated with the Cumulative Illness Rating Scale were significantly associated with all the muscle measurements: ALSTI (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.07–1.26, P < 0.001), masseter (OR 1.16, 95% CI 1.07–1.26, P < 0.001) and tongue (OR 1.13, 95% CI 1.04–1.22, P = 0.002); the higher the comorbidities, the higher the probability of having abnormal muscle mass. Conclusions: ALSTI was significantly correlated with tongue and masseter muscle mass. When performing the sarcopenia diagnostic algorithm, the prevalence of sarcopenia calculated with head muscles did not differ from sarcopenia calculated using DXA, and almost all participants were correctly classified using both methods.
|
|
| 7. |
|
|
| 8. |
- Bousquet, Jean, et al.
(författare)
-
Allergic Rhinitis and its Impact on Asthma (ARIA) Phase 4 (2018) : Change management in allergic rhinitis and asthma multimorbidity using mobile technology
- 2019
-
Ingår i: Journal of Allergy and Clinical Immunology. - : Elsevier. - 0091-6749 .- 1097-6825. ; 143:3, s. 864-879
-
Tidskriftsartikel (refereegranskat)abstract
- Allergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline by using the best approach to integrated care pathways using mobile technology in patients with allergic rhinitis (AR) and asthma multimorbidity. The proposed next phase of ARIA is change management, with the aim of providing an active and healthy life to patients with rhinitis and to those with asthma multimorbidity across the lifecycle irrespective of their sex or socioeconomic status to reduce health and social inequities incurred by the disease. ARIA has followed the 8-step model of Kotter to assess and implement the effect of rhinitis on asthma multimorbidity and to propose multimorbid guidelines. A second change management strategy is proposed by ARIA Phase 4 to increase self-medication and shared decision making in rhinitis and asthma multimorbidity. An innovation of ARIA has been the development and validation of information technology evidence-based tools (Mobile Airways Sentinel Network [MASK]) that can inform patient decisions on the basis of a self-care plan proposed by the health care professional.
|
|
| 9. |
- Brinkmalm, Gunnar, et al.
(författare)
-
An online nano-LC-ESI-FTICR-MS method for comprehensive characterization of endogenous fragments from amyloid β and amyloid precursor protein in human and cat cerebrospinal fluid.
- 2012
-
Ingår i: Journal of mass spectrometry : JMS. - : Wiley. - 1096-9888 .- 1076-5174. ; 47:5, s. 591-603
-
Tidskriftsartikel (refereegranskat)abstract
- Amyloid precursor protein (APP) is the precursor protein to amyloid β (Aβ), the main constituent of senile plaques in Alzheimer's disease (AD). Endogenous Aβ peptides reflect the APP processing, and greater knowledge of different APP degradation pathways is important to understand the mechanism underlying AD pathology. When one analyzes longer Aβ peptides by low-energy collision-induced dissociation tandem mass spectrometry (MS/MS), mainly long b-fragments are observed, limiting the possibility to determine variations such as amino acid variants or post-translational modifications (PTMs) within the N-terminal half of the peptide. However, by using electron capture dissociation (ECD), we obtained a more comprehensive sequence coverage for several APP/Aβ peptide species, thus enabling a deeper characterization of possible variants and PTMs. Abnormal APP/Aβ processing has also been described in the lysosomal storage disease Niemann-Pick type C and the major large animal used for studying this disease is cat. By ECD MS/MS, a substitution of Asp7 → Glu in cat Aβ was identified. Further, sialylated core 1 like O-glycans at Tyr10, recently discovered in human Aβ (a previously unknown glycosylation type), were identified also in cat cerebrospinal fluid (CSF). It is therefore likely that this unusual type of glycosylation is common for (at least) species belonging to the magnorder Boreoeutheria. We here describe a detailed characterization of endogenous APP/Aβ peptide species in CSF by using an online top-down MS-based method.
|
|
| 10. |
- Brusini, Irene
(författare)
-
Methods for the analysis and characterization of brain morphology from MRI images
- 2022
-
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.
|
|
