| 1. |
- Hibar, Derrek P., et al.
(author)
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Novel genetic loci associated with hippocampal volume
- 2017
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
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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.
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| 3. |
- Thompson, PM, et al.
(author)
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ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
- 2020
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In: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 100-
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Journal article (peer-reviewed)abstract
- This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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| 6. |
- Dress A, Grunewald S, Gutman I, Lepovic M, Vidovic D
(author)
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On the number of walks in trees
- 2003
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In: MATCH-COMMUNICATIONS IN MATHEMATICAL AND IN COMPUTER CHEMISTRY. - 0340-6253. ; :48, s. 63-85
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Journal article (peer-reviewed)
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| 7. |
- 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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| 8. |
- Gutman, I., et al.
(author)
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Estimating and approximating the total pi-electron energy of benzenoid hydrocarbons
- 2000
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In: Zeitschrift fur Naturforschung A-A Journal of Physical Sciences. - 0932-0784 .- 1865-7109. ; 55:5, s. 507-512
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Journal article (peer-reviewed)abstract
- Lower and upper bounds as well as approximate formulas for the total pi-electron energy (E) of benzenoid hydrocarbons are deduced, depending only on the number of carbon atoms (n) and number of carbon-carbon bonds (m). These are better than the several previously known (n, m)-type estimates and approximations for E.
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| 9. |
- Jack, C. R., et al.
(author)
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Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2
- 2015
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In: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 11:7, s. 740-756
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Journal article (peer-reviewed)abstract
- Introduction: Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. Methods: We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. Results: Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. Discussion: Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future. (C) 2015 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association.
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| 10. |
- Koolen, J. H., et al.
(author)
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Improving the McClelland inequality for total pi-electron energy
- 2000
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In: Chemical Physics Letters. - 0009-2614 .- 1873-4448. ; 320:3-4, s. 213-216
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Journal article (peer-reviewed)abstract
- The McClelland inequality, E less than or equal to root 2mn, estimates the total pi-electron energy (E) of a conjugated hydrocarbon by means of the number of carbon atoms (n) and the number of carbon-carbon bonds (m). We now show that in the general case 2m/n + root(n - 1)(2m - 4m(2)/n(2)) is a better (n,m)-type upper bound for E. An even better estimate, 4m/n + root(n - 2)(2m - 8m(2)/n(2)), holds for alternant hydrocarbons. (C) 2000 Elsevier Science B.V. All rights reserved.
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