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- Ge, R, et al.
(författare)
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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
- 2023
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Ingår i: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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- Kelkka, T, et al.
(författare)
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Anti-COX-2 autoantibody is a novel biomarker of immune aplastic anemia
- 2022
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Ingår i: Leukemia. - : Springer Science and Business Media LLC. - 1476-5551 .- 0887-6924. ; 36:9, s. 2317-2327
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Tidskriftsartikel (refereegranskat)abstract
- In immune aplastic anemia (IAA), severe pancytopenia results from the immune-mediated destruction of hematopoietic stem cells. Several autoantibodies have been reported, but no clinically applicable autoantibody tests are available for IAA. We screened autoantibodies using a microarray containing >9000 proteins and validated the findings in a large international cohort of IAA patients (n = 405) and controls (n = 815). We identified a novel autoantibody that binds to the C-terminal end of cyclooxygenase 2 (COX-2, aCOX-2 Ab). In total, 37% of all adult IAA patients tested positive for aCOX-2 Ab, while only 1.7% of the controls were aCOX-2 Ab positive. Sporadic non-IAA aCOX-2 Ab positive cases were observed among patients with related bone marrow failure diseases, multiple sclerosis, and type I diabetes, whereas no aCOX-2 Ab seropositivity was detected in the healthy controls, in patients with non-autoinflammatory diseases or rheumatoid arthritis. In IAA, anti-COX-2 Ab positivity correlated with age and the HLA-DRB1*15:01 genotype. 83% of the >40 years old IAA patients with HLA-DRB1*15:01 were anti-COX-2 Ab positive, indicating an excellent sensitivity in this group. aCOX-2 Ab positive IAA patients also presented lower platelet counts. Our results suggest that aCOX-2 Ab defines a distinct subgroup of IAA and may serve as a valuable disease biomarker.
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- Mizumaki, H, et al.
(författare)
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A frequent nonsense mutation in exon 1 across certain HLA-A and -B alleles in leukocytes of patients with acquired aplastic anemia
- 2021
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Ingår i: Haematologica. - : Ferrata Storti Foundation (Haematologica). - 1592-8721 .- 0390-6078. ; 106:6, s. 1581-1590
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Tidskriftsartikel (refereegranskat)abstract
- Leukocytes that lack HLA allelic expression are frequently detected in patients with acquired aplastic anemia (AA) who respond to immunosuppressive therapy (IST), although the exact mechanisms underlying the HLA loss and HLA allele repertoire likely to acquire loss-of-function mutations are unknown. We identified a common nonsense mutation at position 19 (c.19C>T, p.R7X) in exon 1 (Exon1mut) of different HLA-A and -B alleles in HLA-lacking granulocytes from AA patients. A droplet digital PCR (ddPCR) assay capable of detecting as few as 0.07% Exon1mut HLA alleles in total DNA revealed the mutation was present in 29% (101/353) of AA patients, with a median allele frequency of 0.42% (range, 0.071% to 21.3%). Exon1mut occurred in only 12 different HLA-A (n=4) and HLA-B (n=8) alleles, including B*40:02 (n=31) and A*02:06 (n=15), which correspond to 4 HLA supertypes (A02, A03, B07, and B44). The percentages of patients who possessed at least one of these 12 HLA alleles were significantly higher in the 353 AA patients (92%, P
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- Bruin, WB, et al.
(författare)
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Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters
- 2020
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Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 342-
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Tidskriftsartikel (refereegranskat)abstract
- No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.
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- Dima, Danai, et al.
(författare)
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Subcortical volumes across the lifespan : Data from 18,605 healthy individuals aged 3-90 years.
- 2022
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 452-469
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Tidskriftsartikel (refereegranskat)abstract
- Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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- Frangou, Sophia, et al.
(författare)
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Cortical thickness across the lifespan : Data from 17,075 healthy individuals aged 3-90 years
- 2022
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Ingår i: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 431-451
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Tidskriftsartikel (refereegranskat)abstract
- Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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