1. |
- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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2. |
- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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3. |
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4. |
- Mullins, N., et al.
(author)
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Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
- 2021
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 53, s. 817-829
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Journal article (peer-reviewed)abstract
- Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.
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5. |
- Sønderby, Ida E., et al.
(author)
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1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans
- 2021
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In: Translational Psychiatry. - : Nature Publishing Group. - 2158-3188. ; 11:1
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Journal article (peer-reviewed)abstract
- Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
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6. |
- van der Meer, Dennis, et al.
(author)
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Association of Copy Number Variation of the 15q11.2 BP1-BP2 Region With Cortical and Subcortical Morphology and Cognition
- 2020
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In: JAMA psychiatry. - : American Medical Association (AMA). - 2168-6238 .- 2168-622X. ; 77:4, s. 420-430
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Journal article (peer-reviewed)abstract
- Importance: Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities.Objective: To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance.Design, Setting, and Participants: In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019.Main Outcomes and Measures: The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort.Results: Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = -0.41; SE, 0.08; P = 4.9 × 10-8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10-7), and a smaller nucleus accumbens (Cohen d = -0.27; SE, 0.07; P = 7.3 × 10-5). There was also a significant negative dose response on cortical thickness (β = -0.24; SE, 0.05; P = 6.8 × 10-7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks.Conclusions and Relevance: These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders.
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7. |
- Sonderby, Ida E., et al.
(author)
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Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia
- 2020
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In: Molecular Psychiatry. - : Nature Publishing Group. - 1359-4184 .- 1476-5578. ; 25:3, s. 584-602
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Journal article (peer-reviewed)abstract
- Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = −0.71 to −1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = −0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10−6, 1.7 × 10−9, 3.5 × 10−12 and 1.0 × 10−4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.
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- Mikocka-Walus, Antonina, et al.
(author)
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Exploring the Relationship Between Self-Isolation and Distress Among People with Gastrointestinal Disorders During the COVID-19 Pandemic
- 2022
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In: Journal of clinical psychology in medical settings. - : Springer. - 1068-9583 .- 1573-3572. ; 29:3, s. 654-665
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Journal article (peer-reviewed)abstract
- This study aimed to explore the association between perceived isolation and symptoms of distress in people with GI disorders at the time of the pandemic; and to examine factors which moderate this relationship. This online cross-sectional survey was advertised in May-September 2020 via patient organisations and associated social media. Overall, 831 people (82% female, mean age 49 years) from 27 countries participated. A significant relationship between social isolation and psychological distress was noted (r = .525, p < .001). GI symptoms moderated the association between isolation and distress (B = .047, t = 2.47, p = .015). Interventions targeting these factors may help to reduce distress in people with GI disorders at the time of major stressors such as the COVID-19 pandemic.
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9. |
- Brown, Brielin C., et al.
(author)
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Multiset correlation and factor analysis enables exploration of multi-omics data
- 2023
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In: Cell Genomics. - : Elsevier BV. - 2666-979X. ; 3:8, s. 100359-
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Journal article (peer-reviewed)abstract
- Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.
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10. |
- Braun, Gabriel A., et al.
(author)
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On the Mechanism of Self-Assembly by a Hydrogel-Forming Peptide
- 2020
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In: Biomacromolecules. - : American Chemical Society (ACS). - 1525-7797 .- 1526-4602. ; 21:12, s. 4781-4794
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Journal article (peer-reviewed)abstract
- Self-assembling peptide-based hydrogels are a class of tunable soft materials that have been shown to be highly useful for a number of biomedical applications. The dynamic formation of the supramolecular fibrils that compose these materials has heretofore remained poorly characterized. A better understanding of this process would provide important insights into the behavior of these systems and could aid in the rational design of new peptide hydrogels. Here, we report the determination of the microscopic steps that underpin the self-assembly of a hydrogel-forming peptide, SgI37-49. Using theoretical models of linear polymerization to analyze the kinetic self-assembly data, we show that SgI37-49 fibril formation is driven by fibril-catalyzed secondary nucleation and that all the microscopic processes involved in SgI37-49 self-assembly display an enzyme-like saturation behavior. Moreover, this analysis allows us to quantify the rates of the underlying processes at different peptide concentrations and to calculate the time evolution of these reaction rates over the time course of self-assembly. We demonstrate here a new mechanistic approach for the study of self-assembling hydrogel-forming peptides, which is complementary to commonly used materials science characterization techniques.
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