| 1. |
- 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. |
- Dima, Danai, et al.
(author)
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Subcortical volumes across the lifespan : Data from 18,605 healthy individuals aged 3-90 years.
- 2022
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In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 452-469
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Journal article (peer-reviewed)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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| 3. |
- Frangou, Sophia, et al.
(author)
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Cortical thickness across the lifespan : Data from 17,075 healthy individuals aged 3-90 years
- 2022
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In: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 431-451
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Journal article (peer-reviewed)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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| 4. |
- Gutman, Boris A, et al.
(author)
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A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium
- 2022
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In: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 352-372
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Journal article (peer-reviewed)abstract
- Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
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| 5. |
- Petrov, Dmitry, et al.
(author)
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Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
- 2017
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In: Machine learning in medical imaging. MLMI (Workshop). - Cham : Springer International Publishing. ; 10541, s. 371-378
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Journal article (peer-reviewed)abstract
- As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability.
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| 6. |
- Wierenga, Lara M., et al.
(author)
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Greater male than female variability in regional brain structure across the lifespan
- 2022
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In: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 470-499
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Journal article (peer-reviewed)abstract
- For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
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| 7. |
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| 8. |
- Kaufmann, Tobias, et al.
(author)
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Common brain disorders are associated with heritable patterns of apparent aging of the brain
- 2019
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In: Nature Neuroscience. - : Nature Publishing Group. - 1097-6256 .- 1546-1726. ; 22:10, s. 1617-
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Journal article (peer-reviewed)abstract
- Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.
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| 9. |
- Solmi, Marco, et al.
(author)
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Risk and protective factors for cannabis, cocaine, and opioid use disorders : An umbrella review of meta-analyses of observational studies
- 2021
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In: Neuroscience and Biobehavioral Reviews. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0149-7634 .- 1873-7528. ; 126, s. 243-251
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Research review (peer-reviewed)abstract
- Several meta-analyses of observational studies have addressed the association between risk and protective factors and cannabis/cocaine/opioid use disorders, but results are conflicting. No umbrella review has ever graded the credibility of this evidence (not significant/weak/suggestive/highly suggestive/convincing). We searched Pubmed-MEDLINE/PsycInfo, last search September 21, 2020. We assessed the quality of meta-analyses with the AMSTAR-2 tool. Out of 3,072 initial references, five were included, providing 19 associations between 12 putative risk/protective factors and cannabis/cocaine/opioid use disorders (cases: 4539; N = 1,118,872,721). While 84 % of the associations were statistically significant, none was convincing. One risk factor (smoking) had highly suggestive evidence for association with nonmedical use of prescription opioid medicines (OR = 3.07, 95 %CI:2.27 to 4.14). Convincing evidence emerged in sensitivity analyses on antisocial behavior and cannabis use disoder (OR 3.34, 95 %CI 2.53-4.41). Remaining associations had weak evidence. The quality of meta-analyses was rated as moderate in two (40 %), low in one (20 %), and critically low in two (40 %). Future research is needed to better profile risk/protective factors for cannabis/cocaine/opioid use disorders disorders informing preventive approaches.
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| 10. |
- Solmi, Marco, et al.
(author)
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Risk and Protective Factors for Personality Disorders : An Umbrella Review of Published Meta-Analyses of Case-Control and Cohort Studies
- 2021
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In: Frontiers in Psychiatry. - : Frontiers Media SA. - 1664-0640. ; 12
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Research review (peer-reviewed)abstract
- The putative risk/protective factors for several personality disorders remain unclear. The vast majority of published studies has assessed personality characteristics/traits rather than disorders. Thus, the current umbrella review of meta-analyses (MAs) aims to systematically assess risk or protective factors associated with personality disorders. We searched PubMed-MEDLINE/PsycInfo databases, up to August 31, 2020. Quality of MAs was assessed with AMSTAR-2, while the credibility of evidence for each association was assessed through standard quantitative criteria. Out of 571 initial references, five meta-analyses met inclusion criteria, encompassing 56 associations of 26 potential environmental factors for antisocial, dependent, borderline personality disorder, with a median of five studies per association, and median 214 cases per association. Overall, 35 (62.5%) of the associations were nominally significant. Six associations met class II (i.e., highly suggestive) evidence for borderline personality disorder, with large effect sizes involving childhood emotional abuse (OR = 28.15, 95% CI 14.76-53.68), childhood emotional neglect (OR = 22.86, 95% CI 11.55-45.22), childhood any adversities (OR = 14.32, 95% CI 10.80-18.98), childhood physical abuse (OR = 9.30, 95% CI 6.57-13.17), childhood sexual abuse (OR = 7.95, 95% CI 6.21-10.17), and childhood physical neglect (OR = 5.73, 95% CI 3.21-10.21), plus 16 further associations supported by class IV evidence. No risk factor for antisocial or dependent personality disorder was supported by class I, II, and III, but six and seven met class IV evidence, respectively. Quality of included meta-analyses was rated as moderate in two, critically low in three. The large effect sizes found for a broad range of childhood adversities suggest that prevention of personality disorders should target childhood-related risk factors. However, larger cohort studies assessing multidimensional risk factors are needed in the field.
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