| 1. |
- Burger, Antoinette, et al.
(författare)
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The impact of acute and short-term methamphetamine abstinence on brain metabolites : A proton magnetic resonance spectroscopy chemical shift imaging study
- 2018
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Ingår i: Drug And Alcohol Dependence. - : Elsevier BV. - 0376-8716 .- 1879-0046. ; 185, s. 226-237
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundAbuse of methamphetamine (MA) is a global health concern. Previous H-1-MRS studies have found that, with methamphetamine abstinence (MAA), there are changes in n-acetyl-aspartate (NAA/Cr), myo-inositol (mI/Cr), choline (Cho/Cr and Cho/NAA), and glutamate with glutamine (Glx) metabolites. Limited studies have investigated the effect of acute MAA, and acute-to-short-term MAA on brain metabolites.MethodsAdults with chronic MA dependence (n = 31) and healthy controls (n = 22) were recruited. Two-dimensional chemical shift H-1-MRS imaging (TR2000 ms, TE30 ms) slice was performed and included voxels in bilateral anterior-cingulate (ACC), frontal-white-matter (FWM), and dorsolateral-prefrontal-cortices (DLPFC). Control participants were scanned once. The MA group was scanned twice, with acute (1.5 +/- 0.6 weeks, n = 31) and short-term MAA (5.1 +/- 0.8 weeks, n = 22). The change in H-1-MRS metabolites over time (n = 19) was also investigated. Standard H-1-MRS metabolites are reported relative to Cr + PCr.ResultsAcute MAA showed lower n-acetyl-aspartate (NAA) and n-acetyl-aspartate with n-acetyl-aspartyl-glutamate (NAA + NAAG) in left DLPFC, and glycerophosphocholine with phosphocholine (GPC + PCh) in left FWM. Short-term MAA showed lower NAA + NAAG and higher myo-inositol (mI) in right ACC, lower NAA and NAA + NAAG in the left DLPFC, and lower GPC + PCh in left FWM. Over time, MAA showed decreased NAA and NAA + NAAG and increased mI in right ACC, decreased NAA and NAA + NAAG in right FWM, and decreased in mI in left FWM.ConclusionIn acute MAA, there was damage to the integrity of neuronal tissue, which was enhanced with short-term MAA. From acute to short-term MAA, activation of neuroinflammatory processes are suggested. This is the first H-1-MRS study to report the development of neuroinflammation with loss of neuronal integrity in MAA.
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| 2. |
- 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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| 3. |
- Fountoulakis, Konstantinos N., et al.
(författare)
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Gender, age at onset, and duration of being ill as predictors for the long-term course and outcome of schizophrenia : an international multicenter study
- 2022
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Ingår i: CNS Spectrums. - : CAMBRIDGE UNIV PRESS. - 1092-8529 .- 2165-6509. ; 27:6, s. 716-723
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Tidskriftsartikel (refereegranskat)abstract
- Background The aim of the current study was to explore the effect of gender, age at onset, and duration on the long-term course of schizophrenia. Methods Twenty-nine centers from 25 countries representing all continents participated in the study that included 2358 patients aged 37.21 +/- 11.87 years with a DSM-IV or DSM-5 diagnosis of schizophrenia; the Positive and Negative Syndrome Scale as well as relevant clinicodemographic data were gathered. Analysis of variance and analysis of covariance were used, and the methodology corrected for the presence of potentially confounding effects. Results There was a 3-year later age at onset for females (P < .001) and lower rates of negative symptoms (P < .01) and higher depression/anxiety measures (P < .05) at some stages. The age at onset manifested a distribution with a single peak for both genders with a tendency of patients with younger onset having slower advancement through illness stages (P = .001). No significant effects were found concerning duration of illness. Discussion Our results confirmed a later onset and a possibly more benign course and outcome in females. Age at onset manifested a single peak in both genders, and surprisingly, earlier onset was related to a slower progression of the illness. No effect of duration has been detected. These results are partially in accord with the literature, but they also differ as a consequence of the different starting point of our methodology (a novel staging model), which in our opinion precluded the impact of confounding effects. Future research should focus on the therapeutic policy and implications of these results in more representative samples.
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| 4. |
- Fountoulakis, Konstantinos N., et al.
(författare)
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Staging of Schizophrenia With the Use of PANSS : An International Multi-Center Study
- 2019
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Ingår i: International Journal of Neuropsychopharmacology. - : Oxford University Press. - 1461-1457 .- 1469-5111. ; 22:11, s. 681-697
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionA specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method.MethodsTwenty-nine centers from 25 countries contributed 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed.ResultsExploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified >85% of patients.DiscussionThis study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time.
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| 5. |
- 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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| 6. |
- Gutman, Boris A, et al.
(författare)
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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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Ingår i: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 43:1, s. 352-372
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Tidskriftsartikel (refereegranskat)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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| 7. |
- McWhinney, Sean R, et al.
(författare)
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Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.
- 2021
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Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 26:11, s. 6806-6819
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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 mediated by 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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| 8. |
- McWhinney, Sean R, et al.
(författare)
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Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.
- 2022
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Ingår i: Bipolar disorders. - : Wiley. - 1399-5618 .- 1398-5647. ; 24:5, s. 509-520
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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 14 sites 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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| 9. |
- McWhinney, Sean R, et al.
(författare)
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Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.
- 2023
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Ingår i: Psychological medicine. - 1469-8978. ; , s. 1-11
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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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| 10. |
- Petrov, Dmitry, et al.
(författare)
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Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
- 2017
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Ingår i: Machine learning in medical imaging. MLMI (Workshop). - Cham : Springer International Publishing. ; 10541, s. 371-378
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Tidskriftsartikel (refereegranskat)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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