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Search: WFRF:(Wee S.)

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  • Landén, Mikael, 1966, et al. (author)
  • Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
  • 2021
  • In: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 5124-5139
  • Journal article (peer-reviewed)abstract
    • Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d = 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates. © 2020, The Author(s).
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  • 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.
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  • 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.
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  • Thompson, PM, et al. (author)
  • ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
  • 2020
  • In: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 100-
  • 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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  • 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.
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  • Result 1-10 of 59
Type of publication
journal article (54)
conference paper (4)
research review (1)
Type of content
peer-reviewed (56)
other academic/artistic (3)
Author/Editor
Thompson, Paul M (9)
Jahanshad, Neda (9)
van der Wee, Nic J. ... (8)
Ahmed, Naeem (8)
Siow, Kim S. (8)
Patra, Anuttam (8)
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Ching, Christopher R ... (7)
Jahanshad, N (7)
Schmaal, L (7)
Veltman, DJ (7)
Thompson, PM (6)
Wittfeld, K (6)
Andersson, Micael (6)
Gruber, O (6)
Van der Wee, NJA (6)
Aghajani, Moji (6)
Franke, Barbara (5)
Andreassen, OA (5)
Agartz, Ingrid (5)
Brouwer, Rachel M (5)
Grotegerd, Dominik (5)
Thomopoulos, Sophia ... (5)
Westlye, Lars T (5)
Andreassen, Ole A (5)
MCDONALD, C (5)
Hibar, DP (5)
Renteria, ME (5)
Ching, CRK (5)
Ehrlich, S (5)
Hoogman, M (5)
Walton, E (5)
Buitelaar, JK (5)
Glahn, DC (5)
Grabe, HJ (5)
Hosten, N (5)
Kochunov, P (5)
McIntosh, AM (5)
Turner, JA (5)
Van Haren, NEM (5)
Volzke, H (5)
Walter, H (5)
Schumann, G (5)
Franke, B (5)
Masood, Asad (5)
de Geus, Eco J. C. (5)
Martin, Nicholas G. (5)
Boomsma, Dorret I. (5)
Meyer-Lindenberg, An ... (5)
Heinz, Andreas (5)
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Karolinska Institutet (32)
Uppsala University (12)
Luleå University of Technology (8)
University of Gothenburg (7)
Umeå University (7)
Stockholm University (6)
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Lund University (5)
Linköping University (3)
Linnaeus University (2)
Royal Institute of Technology (1)
Jönköping University (1)
Mid Sweden University (1)
Chalmers University of Technology (1)
RISE (1)
Swedish University of Agricultural Sciences (1)
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Language
English (59)
Research subject (UKÄ/SCB)
Medical and Health Sciences (21)
Natural sciences (18)
Social Sciences (4)
Engineering and Technology (3)
Humanities (1)

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