1. |
|
|
2. |
- Hibar, Derrek P., et al.
(author)
-
Novel genetic loci associated with hippocampal volume
- 2017
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
-
Journal article (peer-reviewed)abstract
- The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r(g) = -0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
|
|
3. |
- Satizabal, Claudia L., et al.
(author)
-
Genetic architecture of subcortical brain structures in 38,851 individuals
- 2019
-
In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:11, s. 1624-
-
Journal article (peer-reviewed)abstract
- Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
|
|
4. |
- Thompson, Paul M., et al.
(author)
-
The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
- 2014
-
In: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
-
Journal article (peer-reviewed)abstract
- The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
|
|
5. |
- Wierenga, Lara M., et al.
(author)
-
Greater male than female variability in regional brain structure across the lifespan
- 2022
-
In: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 470-499
-
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.
|
|
6. |
- Dima, Danai, et al.
(author)
-
Subcortical volumes across the lifespan : Data from 18,605 healthy individuals aged 3-90 years.
- 2022
-
In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 452-469
-
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.
|
|
7. |
- Frangou, Sophia, et al.
(author)
-
Cortical thickness across the lifespan : Data from 17,075 healthy individuals aged 3-90 years
- 2022
-
In: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 431-451
-
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.
|
|
8. |
- Belov, Vladimir, et al.
(author)
-
Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
- 2024
-
In: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 14:1
-
Journal article (peer-reviewed)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.
|
|
9. |
- Hilbert, Kevin, et al.
(author)
-
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
-
In: The American Journal of Psychiatry. - 1535-7228. ; 181:8, s. 728-740
-
Journal article (peer-reviewed)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.
|
|
10. |
- Bas-Hoogendam, Janna Marie, et al.
(author)
-
Voxel-based morphometry multi-center mega-analysis of brain structure in social anxiety disorder
- 2017
-
In: NeuroImage. - : Elsevier BV. - 2213-1582. ; 16, s. 678-688
-
Journal article (peer-reviewed)abstract
- Social anxiety disorder (SAD) is a prevalent and disabling mental disorder, associated with significant psychiatric co-morbidity. Previous research on structural brain alterations associated with SAD has yielded inconsistent results concerning the direction of the changes in gray matter (GM) in various brain regions, as well as on the relationship between brain structure and SAD-symptomatology. These heterogeneous findings are possibly due to limited sample sizes. Multi-site imaging offers new opportunities to investigate SAD-related alterations in brain structure in larger samples.An international multi-center mega-analysis on the largest database of SAD structural T1-weighted 3T MRI scans to date was performed to compare GM volume of SAD-patients (n = 174) and healthy control (HC)-participants (n = 213) using voxel-based morphometry. A hypothesis-driven region of interest (ROI) approach was used, focusing on the basal ganglia, the amygdala-hippocampal complex, the prefrontal cortex, and the parietal cortex. SAD-patients had larger GM volume in the dorsal striatum when compared to HC-participants. This increase correlated positively with the severity of self-reported social anxiety symptoms. No SAD-related differences in GM volume were present in the other ROIs. Thereby, the results of this mega-analysis suggest a role for the dorsal striatum in SAD, but previously reported SAD-related changes in GM in the amygdala, hippocampus, precuneus, prefrontal cortex and parietal regions were not replicated. Our findings emphasize the importance of large sample imaging studies and the need for meta-analyses like those performed by the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium.
|
|
11. |
- Groenewold, Nynke A., et al.
(author)
-
Volume of subcortical brain regions in social anxiety disorder : mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group
- 2023
-
In: Molecular Psychiatry. - : Springer Nature. - 1359-4184 .- 1476-5578. ; 28:3, s. 1079-1089
-
Journal article (peer-reviewed)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.
|
|
12. |
|
|
13. |
- Bas-Hoogendam, Janna Marie, et al.
(author)
-
ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders
- 2022
-
In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 43:1, s. 83-112
-
Research review (peer-reviewed)abstract
- Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.
|
|
14. |
- Chye, Yann, et al.
(author)
-
Subcortical surface morphometry in substance dependence : An ENIGMA addiction working group study
- 2020
-
In: Addiction Biology. - : WILEY. - 1355-6215 .- 1369-1600. ; 25:6
-
Journal article (peer-reviewed)abstract
- While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.
|
|
15. |
- Petrov, Dmitry, et al.
(author)
-
Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
- 2017
-
In: Machine learning in medical imaging. MLMI (Workshop). - Cham : Springer International Publishing. ; 10541, s. 371-378
-
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.
|
|
16. |
- Wolfensberger, Saskia P, et al.
(author)
-
Quantification of the neurokinin 1 receptor ligand [¹¹C]R116301
- 2011
-
In: Nuclear medicine communications. - 0143-3636 .- 1473-5628. ; 32:10, s. 896-902
-
Journal article (peer-reviewed)abstract
- PURPOSE:Neurokinin 1 (NK1) receptors have been implicated in depression, anxiety, and pain perception. Recently, it was shown that, in the human brain, a specific NK1 receptor-related signal was obtained with the novel radioligand, [¹¹C]R116301, using positron emission tomography. The purpose of this study was to evaluate various methods for quantifying specific [¹¹C]R116301 binding.METHODS:Two dynamic 90-min [¹¹C]R116301 scans, separated by 5 h, were performed in 11 healthy volunteers. In three patients, the second scan was performed after an oral blocking dose of 125 mg of aprepitant, whereas in the other eight, no intervention was performed (test-retest). Whole striatum was used as the tissue of interest, as it has the highest density of NK1 receptors. Cerebellum was used as the reference tissue.RESULTS:Reference tissue models were stable with the simplified reference tissue model (SRTM) performing best. Average (± standard deviation) SRTM-derived mean nondisplaceable binding potential (BP(ND)) of all (first) baseline scans was 0.64±0.31 (n=11), which reduced to -0.01±0.03 (n=3) after aprepitant administration. Test-retest results showed low variability (14.0±10.7%) and excellent reliability, as indicated by the intraclass correlation coefficient (0.93). The ratio of standardized uptake values of striatum and cerebellum minus 1, an approximation of BP(ND), showed very low variability (6.2±3.1%) with excellent reliability (intraclass correlation coefficient=0.98), and correlated well with SRTM-derived BP(ND) (R²=0.96).CONCLUSION:SRTM is the model of choice for quantifying [¹¹C]R116301 binding. Semiquantitative tissue ratios hold promise for routine clinical applications.
|
|