1. |
- Abramowski, A., et al.
(författare)
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HESS J1943+213 : a candidate extreme BL Lacertae object
- 2011
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 529, s. A49-
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Tidskriftsartikel (refereegranskat)abstract
- Context. The H. E. S. S. Cherenkov telescope array has been surveying the Galactic plane for new VHE (>100 GeV) gamma-ray sources. Aims. We report on a newly detected point-like source, HESS J1943+213. This source coincides with an unidentified hard X-ray source IGR J19443+2117, which was proposed to have radio and infrared counterparts. Methods. We combine new H. E. S. S., Fermi/LAT and Nancay Radio Telescope observations with pre-existing non-simultaneous multi-wavelength observations of IGR J19443+2117 and discuss the likely source associations as well as the interpretation as an active galactic nucleus, a gamma-ray binary or a pulsar wind nebula. Results. HESS J1943+213 is detected at the significance level of 7.9 sigma (post-trials) at RA(J2000) = 19(h)43(m)55(s) +/- 1(stat)(s) +/- 1(sys)(s), Dec(J2000) = +21 degrees 18'8 '' +/- 17(stat)'' +/- 20(sys)''. The source has a soft spectrum with photon index Gamma = 3.1 +/- 0.3(stat) +/- 0.2(sys) and a flux above 470 GeV of (1.3 +/- 0.2(stat) +/- 0.3(sys)) x 10(-12) cm(-2) s(-1). There is no Fermi/LAT counterpart down to a flux limit of 6 x 10(-9) cm(-2) s(-1) in the 0.1-100 GeV energy range (95% confidence upper limit calculated for an assumed power-law model with a photon index Gamma = 2.0). The data from radio to VHE gamma-rays do not show any significant variability. Conclusions. The lack of a massive stellar counterpart disfavors the binary hypothesis, while the soft VHE spectrum would be very unusual in case of a pulsar wind nebula. In addition, the distance estimates for Galactic counterparts places them outside of the Milky Way. All available observations favor an interpretation as an extreme, high-frequency peaked BL Lac object with a redshift z > 0.14. This would be the first time a blazar is detected serendipitously from ground-based VHE observations, and the first VHE AGN detected in the Galactic Plane.
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2. |
- Abramowski, A., et al.
(författare)
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A multiwavelength view of the flaring state of PKS 2155-304 in 2006
- 2012
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 539, s. A149-
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Tidskriftsartikel (refereegranskat)abstract
- Context. Multiwavelength (MWL) observations of the blazar PKS 2155-304 during two weeks in July and August 2006, the period when two exceptional flares at very high energies (VHE, E greater than or similar to 100 GeV) occurred, provide a detailed picture of the evolution of its emission. The complete data set from this campaign is presented, including observations in VHE gamma-rays (H.E.S. S.), X-rays (RXTE, Chandra, Swift XRT), optical (Swift UVOT, Bronberg, Watcher, ROTSE), and in the radio band (NRT, HartRAO, ATCA). Optical and radio light curves from 2004 to 2008 are compared to the available VHE data from this period, to put the 2006 campaign into the context of the long-term evolution of the source. Aims. The data set offers a close view of the evolution of the source on different time scales and yields new insights into the properties of the emission process. The predictions of synchrotron self-Compton (SSC) scenarios are compared to the MWL data, with the aim of describing the dominant features in the data down to the hour time scale. Methods. The spectral variability in the X-ray and VHE bands is explored and correlations between the integral fluxes at different wavelengths are evaluated. SSC modelling is used to interpret the general trends of the varying spectral energy distribution. Results. The X-ray and VHE gamma-ray emission are correlated during the observed high state of the source, but show no direct connection with longer wavelengths. The long-term flux evolution in the optical and radio bands is found to be correlated and shows that the source reaches a high state at long wavelengths after the occurrence of the VHE flares. Spectral hardening is seen in the Swift XRT data. Conclusions. The nightly averaged high-energy spectra of the non-flaring nights can be reproduced by a stationary one-zone SSC model, with only small variations in the parameters. The spectral and flux evolution in the high-energy band during the night of the second VHE flare is modelled with multi-zone SSC models, which can provide relatively simple interpretations for the hour time-scale evolution of the high-energy emission, even for such a complex data set. For the first time in this type of source, a clear indication is found for a relation between high activity at high energies and a long-term increase in the low frequency fluxes.
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3. |
- Cearns, M., et al.
(författare)
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- 2022
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Ingår i: British Journal of Psychiatry. - : Royal College of Psychiatrists. - 0007-1250 .- 1472-1465. ; 220:4, s. 219-228
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Tidskriftsartikel (refereegranskat)abstract
- Background Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. Aims To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. Method This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi(+)Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. Results The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. Conclusions Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
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4. |
- Le Clerc, S., et al.
(författare)
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HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders
- 2021
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 x 10(-3); FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
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5. |
- Schubert, K. O., et al.
(författare)
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Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients
- 2021
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Ingår i: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi(+)Gen; ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.
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6. |
- Amare, A. T., et al.
(författare)
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Association of polygenic score for major depression with response to lithium in patients with bipolar disorder
- 2021
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Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 2457-2470
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Tidskriftsartikel (refereegranskat)abstract
- Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi(+)Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.
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7. |
- Reinbold, C. S., et al.
(författare)
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Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder
- 2018
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Ingår i: Frontiers in Psychiatry. - : Frontiers Media SA. - 1664-0640. ; 9
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Tidskriftsartikel (refereegranskat)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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8. |
- Scott, J., et al.
(författare)
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Prospective cohort study of early biosignatures of response to lithium in bipolar-I-disorders: overview of the H2020-funded R-LiNK initiative
- 2019
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Ingår i: International Journal of Bipolar Disorders. - : Springer Science and Business Media LLC. - 2194-7511. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Greater precision in the early identification of individuals who are likely to respond to lithium is a significant unmet clinical need. Structure The H2020-funded Response to Lithium Network (R-LiNK; ) will undertake a prospective cohort study of over 300 individuals with bipolar-I-disorder who have agreed to commence a trial of lithium treatment following a recommendation by their treating clinician. The study aims to examine the early prediction of lithium response, non-response and tolerability by combining systematic clinical syndrome subtyping with examination of multi-modal biomarkers (or biosignatures), including omics, neuroimaging, and actigraphy, etc. Individuals will be followed up for 24 months and an independent panel will assess and classify each participants' response to lithium according to predefined criteria that consider evidence of relapse, recurrence, remission, changes in illness activity or treatment failure (e.g. stopping lithium; new prescriptions of other mood stabilizers) and exposure to lithium. Novel elements of this study include the recruitment of a large, multinational, clinically representative sample specifically for the purpose of studying candidate biomarkers and biosignatures; the application of lithium-7 magnetic resonance imaging to explore the distribution of lithium in the brain; development of a digital phenotype (using actigraphy and ecological momentary assessment) to monitor daily variability in symptoms; and economic modelling of the cost-effectiveness of introducing biomarker tests for the customisation of lithium treatment into clinical practice. Also, study participants with sub-optimal medication adherence will be offered brief interventions (which can be delivered via a clinician or smartphone app) to enhance treatment engagement and to minimize confounding of lithium non-response with non-adherence. Conclusions The paper outlines the rationale, design and methodology of the first study being undertaken by the newly established R-LiNK collaboration and describes how the project may help to refine the clinical response phenotype and could translate into the personalization of lithium treatment.
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