| 1. |
- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 2. |
- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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| 3. |
- Niemi, MEK, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 4. |
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| 5. |
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| 6. |
- Ching, C. R. K., et al.
(författare)
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What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group
- 2022
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 56-82
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Tidskriftsartikel (refereegranskat)abstract
- MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.
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| 7. |
- Smol, T., et al.
(författare)
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MED13L-related intellectual disability: involvement of missense variants and delineation of the phenotype
- 2018
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Ingår i: Neurogenetics. - : SPRINGER. - 1364-6745 .- 1364-6753. ; 19:2, s. 93-103
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Tidskriftsartikel (refereegranskat)abstract
- Molecular anomalies in MED13L, leading to haploinsufficiency, have been reported in patients with moderate to severe intellectual disability (ID) and distinct facial features, with or without congenital heart defects. Phenotype of the patients was referred to "MED13L haploinsufficiency syndrome." Missense variants in MED13L were already previously described to cause the MED13L-related syndrome, but only in a limited number of patients. Here we report 36 patients with MED13L molecular anomaly, recruited through an international collaboration between centers of expertise for developmental anomalies. All patients presented with intellectual disability and severe language impairment. Hypotonia, ataxia, and recognizable facial gestalt were frequent findings, but not congenital heart defects. We identified seven de novo missense variations, in addition to protein-truncating variants and intragenic deletions. Missense variants clustered in two mutation hot-spots, i.e., exons 15-17 and 25-31. We found that patients carrying missense mutations had more frequently epilepsy and showed a more severe phenotype. This study ascertains missense variations in MED13L as a cause for MED13L-related intellectual disability and improves the clinical delineation of the condition.
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| 8. |
- Aguilar-Vazquez, A, et al.
(författare)
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Impaired muscle strength is associated with ultrastructure damage in myositis
- 2022
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12:1, s. 17671-
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Tidskriftsartikel (refereegranskat)abstract
- The muscle fiber ultrastructure in Idiopathic Inflammatory Myopathies (IIM) has been scarcely explored, especially in Inclusion Body Myositis. The aim of this study was to implement the Scanning Electron Microscopy (SEM) in a small cohort of IIM patients, together with the characterization of immunological profile for a better understanding of the pathophysiology. For immunological profile characterization, we identified the presence of autoantibodies (Ro-52, OJ, EJ, PL7, PL12, SRP, Jo-1, PMScl75, PMScl100, Ku, SAE1, NXP2, MDA5, TIF1γ, Mi-2α, Mi-2β) and quantified cytokines (IL-1β, IFN-α2, IFN-γ, TNF-α, IL-6, IL-10, IL-12p70, IL-17A, IL-18, IL-23, IL-33) and chemokines (CCL2, CXCL8). The histological analysis was made by hematoxylin–eosin staining while the muscle fiber ultrastructure was characterized by SEM. We observed changes in the morphology and structure of the muscle fiber according to muscle strength and muscle enzymes. We were able to find and describe muscle fiber ultrastructure with marked irregularities, porosities, disruption in the linearity and integrity of the fascicle, more evident in patients with increased serum levels of muscle enzymes and diminished muscle strength. Despite the scarce reports about the use of SEM as a tool in all clinical phenotypes of IIM, our work provides an excellent opportunity to discuss and reframe the clinical usefulness of SEM in the diagnostic approach of IIM.
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| 9. |
- Belov, Vladimir, et al.
(författare)
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Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
- 2024
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.
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| 11. |
- Wang, Y. T., et al.
(författare)
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Regional gastrointestinal transit and pH studied in 215 healthy volunteers using the wireless motility capsule : influence of age, gender, study country and testing protocol
- 2015
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Ingår i: Alimentary Pharmacology and Therapeutics. - : Wiley. - 0269-2813 .- 1365-2036. ; 42:6, s. 761-772
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe wireless motility capsule (WMC) offers the ability to investigate luminal gastrointestinal (GI) physiology in a minimally invasive manner. AimTo investigate the effect of testing protocol, gender, age and study country on regional GI transit times and associated pH values using the WMC. MethodsRegional GI transit times and pH values were determined in 215 healthy volunteers from USA and Sweden studied using the WMC over a 6.5-year period. The effects of test protocol, gender, age and study country were examined. ResultsFor GI transit times, testing protocol was associated with differences in gastric emptying time (GET; shorter with protocol 2 (motility capsule ingested immediately after meal) vs. protocol 1 (motility capsule immediately before): median difference: 52min, P=0.0063) and colonic transit time (CTT; longer with protocol 2: median 140min, P=0.0189), but had no overall effect on whole gut transit time. Females had longer GET (by median 17min, P=0.0307), and also longer CTT by (104min, P=0.0285) and whole gut transit time by (263min, P=0.0077). Increasing age was associated with shorter small bowel transit time (P=0.002), and study country also influenced small bowel and CTTs. Whole gut and CTTs showed clustering of data at values separated by 24h, suggesting that describing these measures as continuous variables is invalid. Testing protocol, gender and study country also significantly influenced pH values. ConclusionsRegional GI transit times and pH values, delineated using the wireless motility capsule (WMC), vary based on testing protocol, gender, age and country. Standardisation of testing is crucial for cross-referencing in clinical practice and future research.
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