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- Schijven, Dick, et al.
(author)
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Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium
- 2023
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences (PNAS). - 0027-8424 .- 1091-6490. ; 120:14
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Journal article (peer-reviewed)abstract
- Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
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| 2. |
- McWhinney, Sean R, et al.
(author)
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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
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In: Human brain mapping. - 1097-0193. ; 45:8
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Journal article (peer-reviewed)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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| 3. |
- Hermanussen, M, et al.
(author)
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Adolescent growth: genes, hormones and the peer group.
- 2014
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In: Pediatric endocrinology reviews : PER. Proceedings of the 20th Aschauer Soiree, held at Glücksburg castle, Germany, 15th to 17th November 2013.. - 1565-4753. ; 11:3, s. 341-53
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Conference paper (peer-reviewed)abstract
- The association between poverty, malnutrition, illness and poor socioeconomic conditions on the one side, and poor growth and short adult stature on the other side, is well recognized. Yet, the simple assumption by implication that poor growth and short stature result from poor living conditions, should be questioned. Recent evidence on the impact of the social network on adolescent growth and adult height further challenges the traditional concept of growth being a mirror of health. Twenty-nine scientists met at Glücksburg castle, Northern Germany, November 15th - 17th 2013, to discuss genetic, endocrine, mathematical and psychological aspects and related issues, of child and adolescent growth and final height.
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| 5. |
- Altomare, D., et al.
(author)
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Plasma biomarkers for Alzheimer's disease: a field-test in a memory clinic
- 2023
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In: Journal of Neurology Neurosurgery and Psychiatry. - 0022-3050. ; 94:6
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Journal article (peer-reviewed)abstract
- Background The key Alzheimer's disease (AD) biomarkers are traditionally measured with techniques/exams that are either expensive (amyloid-positron emission tomography (PET) and tau-PET), invasive (cerebrospinal fluid A beta 42 and p-tau 181), or poorly specific (atrophy on MRI and hypometabolism on fluorodeoxyglucose-PET). Recently developed plasma biomarkers could significantly enhance the efficiency of the diagnostic pathway in memory clinics and improve patient care. This study aimed to: (1) confirm the correlations between plasma and traditional AD biomarkers, (2) assess the diagnostic accuracy of plasma biomarkers as compared with traditional biomarkers, and (3) estimate the proportion of traditional exams potentially saved thanks to the use of plasma biomarkers. Methods Participants were 200 patients with plasma biomarkers and at least one traditional biomarker collected within 12 months. Results Overall, plasma biomarkers significantly correlated with biomarkers assessed through traditional techniques: up to r=0.50 (p<0.001) among amyloid, r=0.43 (p=0.002) among tau, and r=-0.23 (p=0.001) among neurodegeneration biomarkers. Moreover, plasma biomarkers showed high accuracy in discriminating the biomarker status (normal or abnormal) determined by using traditional biomarkers: up to area under the curve (AUC)=0.87 for amyloid, AUC=0.82 for tau, and AUC=0.63 for neurodegeneration status. The use of plasma as a gateway to traditional biomarkers using cohort-specific thresholds (with 95% sensitivity and 95% specificity) could save up to 49% of amyloid, 38% of tau, and 16% of neurodegeneration biomarkers. Conclusion The implementation of plasma biomarkers could save a remarkable proportion of more expensive traditional exams, making the diagnostic workup more cost-effective and improving patient care.
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| 10. |
- Andersen, J. N., et al.
(author)
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Surface core-level shifts of some 4d-metal single-crystal surfaces : Experiments and ab initio calculations
- 1994
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In: Physical Review B (Condensed Matter). - 0163-1829. ; 50:23, s. 17525-17533
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Journal article (peer-reviewed)abstract
- High resolution measurements are reported of the surface core-level shift of the 3d level for the Rh(111), Rh(110), Pd(111), Pd(110), and Ag(111) single-crystal surfaces. These measurements and earlier ones for the Mo(110), Rh(100), and Pd(100) surfaces are analyzed by ab initio calculations of the surface core-level shift. The calculations are found to reproduce well the trends of the experimental shifts with the 4d metal and with the crystal plane. The comparison between these experimental and theoretical results demonstrates the importance of proper inclusion of final-state effects for accurate calculations of surface core-level shifts. A core hole in a surface atom is found to be better screened than one in a bulk atom for the 4d metals to the left of Pd in the Periodic Table. The use of the Z+1 approximation to describe the core hole is investigated both by explicit use of this approximation and by performing calculations for 1s and 3d core holes, respectively. The Z+1 approximation is found to be well obeyed in the case of Ag whereas for the rest of the 4d transition metals it is less precise, introducing errors of typically 0.1 eV.
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