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Sökning: WFRF:(Kircher Martin)

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1.
  • Amare, Azmeraw, et al. (författare)
  • Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.
  • 2023
  • Ingår i: Research square. - : Research Square Platform LLC.
  • Tidskriftsartikel (refereegranskat)abstract
    • Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.
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2.
  • Amare, Azmeraw T, et al. (författare)
  • Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.
  • 2023
  • Ingår i: Molecular psychiatry. - 1476-5578. ; 28, s. 5251-5261
  • Tidskriftsartikel (refereegranskat)abstract
    • Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental healthdisorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P=9.8×10-12, R2=1.9%) and continuous (P=6.4×10-9, R2=2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P=3.9×10-4, R2=0.9%), but not for the continuous outcome (P=0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
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3.
  • Abé, Christoph, et al. (författare)
  • Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group.
  • 2022
  • Ingår i: Biological psychiatry. - : Elsevier BV. - 1873-2402 .- 0006-3223. ; 91:6, s. 582-592
  • Tidskriftsartikel (refereegranskat)abstract
    • Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD.Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables.Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18
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4.
  • Hering, Lars, et al. (författare)
  • Opsins in Onychophora (Velvet Worms) Suggest a Single Origin and Subsequent Diversification of Visual Pigments in Arthropods
  • 2012
  • Ingår i: Molecular biology and evolution. - : Oxford University Press (OUP). - 0737-4038 .- 1537-1719. ; 29:11, s. 3451-3458
  • Tidskriftsartikel (refereegranskat)abstract
    • Multiple visual pigments, prerequisites for color vision, are found in arthropods, but the evolutionary origin of their diversity remains obscure. In this study, we explore the opsin genes in five distantly related species of Onychophora, using deep transcriptome sequencing and screening approaches. Surprisingly, our data reveal the presence of only one opsin gene (onychopsin) in each onychophoran species, and our behavioral experiments indicate a maximum sensitivity of onychopsin to blue-green light. In our phylogenetic analyses, the onychopsins represent the sister group to the monophyletic clade of visual r-opsins of arthropods. These results concur with phylogenomic support for the sister-group status of the Onychophora and Arthropoda and provide evidence for monochromatic vision in velvet worms and in the last common ancestor of Onychophora and Arthropoda. We conclude that the diversification of visual pigments and color vision evolved in arthropods, along with the evolution of compound eyes-one of the most sophisticated visual systems known.
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5.
  • Hilbert, Kevin, et al. (författare)
  • Cortical and Subcortical Brain Alterations in Specific Phobia and Its Animal and Blood-Injection-Injury Subtypes: A Mega-Analysis From the ENIGMA Anxiety Working Group.
  • 2024
  • Ingår i: The American Journal of Psychiatry. - 1535-7228.
  • Tidskriftsartikel (refereegranskat)abstract
    • Specific phobia is a common anxiety disorder, but the literature on associated brain structure alterations exhibits substantial gaps. The ENIGMA Anxiety Working Group examined brain structure differences between individuals with specific phobias and healthy control subjects as well as between the animal and blood-injection-injury (BII) subtypes of specific phobia. Additionally, the authors investigated associations of brain structure with symptom severity and age (youths vs. adults).Data sets from 31 original studies were combined to create a final sample with 1,452 participants with phobia and 2,991 healthy participants (62.7% female; ages 5-90). Imaging processing and quality control were performed using established ENIGMA protocols. Subcortical volumes as well as cortical surface area and thickness were examined in a preregistered analysis.Compared with the healthy control group, the phobia group showed mostly smaller subcortical volumes, mixed surface differences, and larger cortical thickness across a substantial number of regions. The phobia subgroups also showed differences, including, as hypothesized, larger medial orbitofrontal cortex thickness in BII phobia (N=182) compared with animal phobia (N=739). All findings were driven by adult participants; no significant results were observed in children and adolescents.Brain alterations associated with specific phobia exceeded those of other anxiety disorders in comparable analyses in extent and effect size and were not limited to reductions in brain structure. Moreover, phenomenological differences between phobia subgroups were reflected in diverging neural underpinnings, including brain areas related to fear processing and higher cognitive processes. The findings implicate brain structure alterations in specific phobia, although subcortical alterations in particular may also relate to broader internalizing psychopathology.
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6.
  • McWhinney, Sean R, et al. (författare)
  • Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.
  • 2021
  • Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 26:11, s. 6806-6819
  • Tidskriftsartikel (refereegranskat)abstract
    • Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediatedby BMI (Z=2.73, p=0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.
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7.
  • McWhinney, Sean R, et al. (författare)
  • Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.
  • 2022
  • Ingår i: Bipolar disorders. - : Wiley. - 1399-5618 .- 1398-5647. ; 24:5, s. 509-520
  • Tidskriftsartikel (refereegranskat)abstract
    • Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry.We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles.We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex.We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.
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8.
  • McWhinney, Sean R, et al. (författare)
  • Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.
  • 2023
  • Ingår i: Psychological medicine. - 1469-8978. ; 53:14, s. 6743-6753
  • Tidskriftsartikel (refereegranskat)abstract
    • Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.
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9.
  • Chang, Dan, et al. (författare)
  • The evolutionary and phylogeographic history of woolly mammoths : a comprehensive mitogenomic analysis
  • 2017
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • Near the end of the Pleistocene epoch, populations of the woolly mammoth (Mammuthus primigenius) were distributed across parts of three continents, from western Europe and northern Asia through Beringia to the Atlantic seaboard of North America. Nonetheless, questions about the connectivity and temporal continuity of mammoth populations and species remain unanswered. We use a combination of targeted enrichment and high-throughput sequencing to assemble and interpret a data set of 143 mammoth mitochondrial genomes, sampled from fossils recovered from across their Holarctic range. Our dataset includes 54 previously unpublished mitochondrial genomes and significantly increases the coverage of the Eurasian range of the species. The resulting global phylogeny confirms that the Late Pleistocene mammoth population comprised three distinct mitochondrial lineages that began to diverge ~1.0–2.0 million years ago (Ma). We also find that mammoth mitochondrial lineages were strongly geographically partitioned throughout the Pleistocene. In combination, our genetic results and the pattern of morphological variation in time and space suggest that male-mediated gene flow, rather than large-scale dispersals, was important in the Pleistocene evolutionary history of mammoths.
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10.
  • Fors, Carina, et al. (författare)
  • Camera-based sleepiness detection : final report of the project SleepEYE
  • 2011
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • Two literature reviews were conducted in order to identify indicators of driver sleepiness and distraction. Three sleepiness indicators – blink duration, blink frequency and Perclos – were implemented in the camera system.The aims of the study were firstly to develop and evaluate a low cost 1-camera unit for detection of driver impairment, and secondly to identify indicators of driver sleepiness and to create a sleepiness classifier for driving simulators.The project included two experiments. The first was a field test where 18 participants conducted one alert and one sleepy driving session on a motorway. 16 of the 18 participants also participated in the second experiment which was a simulator study similar to the field test.The field test data was used for evaluation of the 1-camera system, with respect to the sleepiness indicators. Blink parameters from the 1-camera system was compared to blink parameters obtained from a reference 3-camera system and from the EOG. It was found that the 1-camera system missed many blinks and that the blink duration was not in agreement with the blink duration obtained from the EOG and from the reference 3-camera system. However, the results also indicated that it should be possible to improve the blink detection algorithm since the raw data looked well in many cases where the algorithm failed to identify blinks.The sleepiness classifier was created using data from the simulator experiment. In the first step, the indicators identified in the literature review were implemented and evaluated. The indicators also included driving and context related parameters in addition to the blink related ones. The most promising indicators were then used as inputs to the classifier.
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11.
  • Gallo, Selene, et al. (författare)
  • Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies
  • 2023
  • Ingår i: Molecular Psychiatry. - : SPRINGERNATURE. - 1359-4184 .- 1476-5578. ; 28:7, s. 3013-3022
  • Tidskriftsartikel (refereegranskat)abstract
    • The promise of machine learning has fueled the hope for developing diagnostic tools for psychiatry. Initial studies showed high accuracy for the identification of major depressive disorder (MDD) with resting-state connectivity, but progress has been hampered by the absence of large datasets. Here we used regular machine learning and advanced deep learning algorithms to differentiate patients with MDD from healthy controls and identify neurophysiological signatures of depression in two of the largest resting-state datasets for MDD. We obtained resting-state functional magnetic resonance imaging data from the REST-meta-MDD (N = 2338) and PsyMRI (N = 1039) consortia. Classification of functional connectivity matrices was done using support vector machines (SVM) and graph convolutional neural networks (GCN), and performance was evaluated using 5-fold cross-validation. Features were visualized using GCN-Explainer, an ablation study and univariate t-testing. The results showed a mean classification accuracy of 61% for MDD versus controls. Mean accuracy for classifying (non-)medicated subgroups was 62%. Sex classification accuracy was substantially better across datasets (73-81%). Visualization of the results showed that classifications were driven by stronger thalamic connections in both datasets, while nearly all other connections were weaker with small univariate effect sizes. These results suggest that whole brain resting-state connectivity is a reliable though poor biomarker for MDD, presumably due to disease heterogeneity as further supported by the higher accuracy for sex classification using the same methods. Deep learning revealed thalamic hyperconnectivity as a prominent neurophysiological signature of depression in both multicenter studies, which may guide the development of biomarkers in future studies.
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12.
  • Groenewold, Nynke A., et al. (författare)
  • Volume of subcortical brain regions in social anxiety disorder : mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group
  • 2023
  • Ingår i: Molecular Psychiatry. - : Springer Nature. - 1359-4184 .- 1476-5578. ; 28:3, s. 1079-1089
  • Tidskriftsartikel (refereegranskat)abstract
    • There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = −0.077, pFWE = 0.037; right: d = −0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = −0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = −0.141, pFWE < 0.001; right: d = −0.158, pFWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.
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13.
  • Javaheripour, Nooshin, et al. (författare)
  • Altered resting-state functional connectome in major depressive disorder : a mega-analysis from the PsyMRI consortium
  • 2021
  • Ingår i: Translational Psychiatry. - : Springer Nature. - 2158-3188. ; 11:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers (). After applying strict exclusion criteria, the final sample consisted of 606 MDD patients (age: 35.8 +/- 11.9 y.o.; females: 60.7%) and 476 healthy participants (age: 33.3 +/- 11.0 y.o.; females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.
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14.
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15.
  • McWhinney, Sean R, et al. (författare)
  • Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.
  • 2024
  • Ingår i: Human brain mapping. - 1097-0193 .- 1097-0193. ; 45:8
  • Tidskriftsartikel (refereegranskat)abstract
    • Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
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16.
  • Ng, Bobby G, et al. (författare)
  • ALG1-CDG: Clinical and Molecular Characterization of 39 Unreported Patients.
  • 2016
  • Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794.
  • Tidskriftsartikel (refereegranskat)abstract
    • Congenital disorders of glycosylation (CDG) arise from pathogenic mutations in over one hundred genes leading to impaired protein or lipid glycosylation. ALG1 encodes a β1,4 mannosyltransferase that catalyzes the addition of the first of nine mannose moieties to form a dolichol-lipid linked oligosaccharide intermediate (DLO) required for proper N-linked glycosylation. ALG1 mutations cause a rare autosomal recessive disorder termed ALG1-CDG. To date thirteen mutations in eighteen patients from fourteen families have been described with varying degrees of clinical severity. We identified and characterized thirty-nine previously unreported cases of ALG1-CDG from thirty-two families and add twenty-six new mutations. Pathogenicity of each mutation was confirmed based on its inability to rescue impaired growth or hypoglycosylation of a standard biomarker in an alg1-deficient yeast strain. Using this approach we could not establish a rank order comparison of biomarker glycosylation and patient phenotype, but we identified mutations with a lethal outcome in the first two years of life. The recently identified protein-linked xeno-tetrasaccharide biomarker, NeuAc-Gal-GlcNAc2 , was seen in all twenty-seven patients tested. Our study triples the number of known patients and expands the molecular and clinical correlates of this disorder. This article is protected by copyright. All rights reserved.
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17.
  • Ng, Bobby G., et al. (författare)
  • DPAGT1 deficiency with encephalopathy (DPAGT1-CDG) : Clinical and genetic description of 11 new patients
  • 2018
  • Ingår i: JIMD Reports. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 2192-8312 .- 2192-8304. ; 44, s. 85-92
  • Bokkapitel (refereegranskat)abstract
    • Pathogenic mutations in DPAGT1 cause a rare type of a congenital disorder of glycosylation termed DPAGT1-CDG or, alternatively, a milder version with only myasthenia known as DPAGT1-CMS. Fourteen disease-causing mutations in 28 patients from 10 families have previously been reported to cause the systemic form, DPAGT1-CDG. We here report on another 11 patients from 8 families and add 10 new mutations. Most patients have a very severe disease course, where common findings are pronounced muscular hypotonia, intractable epilepsy, global developmental delay/intellectual disability, and early death. We also present data on three affected females that are young adults and have a somewhat milder, stable disease. Our findings expand both the molecular and clinical knowledge of previously published data but also widen the phenotypic spectrum of DPAGT1-CDG.
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18.
  • Zhang, Enming, et al. (författare)
  • Dynamic Magnetic Fields Remote-Control Apoptosis via Nanoparticle Rotation.
  • 2014
  • Ingår i: ACS Nano. - : American Chemical Society (ACS). - 1936-086X .- 1936-0851. ; 8:4, s. 3192-3201
  • Tidskriftsartikel (refereegranskat)abstract
    • The ability to control the movement of nanoparticles remotely and with high precision would have far-reaching implications in many areas of nanotechnology. We have designed a unique dynamic magnetic field (DMF) generator that can induce rotational movements of superparamagnetic iron oxide nanoparticles (SPIONs). We examined whether the rotational nanoparticle movement could be used for remote induction of cell death by injuring lysosomal membrane structures. We further hypothesized that the shear forces created by the generation of oscillatory torques (incomplete rotation) of SPIONs bound to lysosomal membranes would cause membrane permeabilization, lead to extravasation of lysosomal contents into the cytoplasm, and induce apoptosis. To this end, we covalently conjugated SPIONs with antibodies targeting the lysosomal protein marker LAMP1 (LAMP1-SPION). Remote activation of slow rotation of LAMP1-SPIONs significantly improved the efficacy of cellular internalization of the nanoparticles. LAMP1-SPIONs then preferentially accumulated along the membrane in lysosomes in both rat insulinoma tumor cells and human pancreatic beta cells due to binding of LAMP1-SPIONs to endogenous LAMP1. Further activation of torques by the LAMP1-SPIONs bound to lysosomes resulted in rapid decrease in size and number of lysosomes, attributable to tearing of the lysosomal membrane by the shear force of the rotationally activated LAMP1-SPIONs. This remote activation resulted in an increased expression of early and late apoptotic markers and impaired cell growth. Our findings suggest that DMF treatment of lysosome-targeted nanoparticles offers a noninvasive tool to induce apoptosis remotely and could serve as an important platform technology for a wide range of biomedical applications.
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