| 1. |
- Aad, G., et al.
(author)
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- 2010
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swepub:Mat__t
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| 2. |
- Aad, G., et al.
(author)
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- 2010
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swepub:Mat__t
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| 3. |
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| 4. |
- Aad, G., et al.
(author)
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- 2010
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swepub:Mat__t
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| 5. |
- Aad, G., et al.
(author)
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- 2011
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swepub:Mat__t
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| 6. |
- Aad, G., et al.
(author)
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- 2010
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swepub:Mat__t
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| 7. |
- Aaltonen, T., et al.
(author)
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Combination of Tevatron Searches for the Standard Model Higgs Boson in the W+W- Decay Mode
- 2010
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In: Physical Review Letters. - 0031-9007 .- 1079-7114. ; 104:6, s. 061802-
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Journal article (peer-reviewed)abstract
- We combine searches by the CDF and D0 Collaborations for a Higgs boson decaying to W+W-. The data correspond to an integrated total luminosity of 4.8 (CDF) and 5.4 (D0) fb(-1) of p (p) over bar collisions at root s = 1.96 TeV at the Fermilab Tevatron collider. No excess is observed above background expectation, and resulting limits on Higgs boson production exclude a standard model Higgs boson in the mass range 162-166 GeV at the 95% C.L.
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| 8. |
- Reinbold, C. S., et al.
(author)
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Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder
- 2018
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In: Frontiers in Psychiatry. - : Frontiers Media SA. - 1664-0640. ; 9
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Journal article (peer-reviewed)abstract
- Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen) Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD associated miRNAs However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGen GWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genome-wide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs in larger GWAS samples of BD and lithium response is warranted.
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| 9. |
- Landén, Mikael, 1966, et al.
(author)
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Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
- 2021
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In: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 5124-5139
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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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