| 61. |
- 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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| 62. |
- Hoshino, Ayuko, et al.
(författare)
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Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers
- 2020
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Ingår i: Cell. - : CELL PRESS. - 0092-8674 .- 1097-4172. ; 182:4, s. 1044-
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Tidskriftsartikel (refereegranskat)abstract
- There is an unmet clinical need for improved tissue and liquid biopsy tools for cancer detection. We investigated the proteomic profile of extracellular vesicles and particles (EVPs) in 426 human samples from tissue explants (TEs), plasma, and other bodily fluids. Among traditional exosome markers, CD9, HSPA8, ALIX, and HSP90AB1 represent pan-EVP markers, while ACTB, MSN, and RAP1B are novel pan-EVP markers. To confirm that EVPs are ideal diagnostic tools, we analyzed proteomes of TE- (n =151) and plasma-derived (n =120) EVPs. Comparison of TE EVPs identified proteins (e.g., VCAN, TNC, and THBS2) that distinguish tumors from normal tissues with 90% sensitivity/94% specificity. Machine-learning classification of plasma-derived EVP cargo, including immunoglobulins, revealed 95% sensitivity/90% specificity in detecting cancer Finally, we defined a panel of tumor-type-specific EVP proteins in TEs and plasma, which can classify tumors of unknown primary origin. Thus, EVP proteins can serve as reliable biomarkers for cancer detection and determining cancer type.
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| 63. |
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| 64. |
- Ou, Anna H., et al.
(författare)
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Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study
- 2024
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Ingår i: TRANSLATIONAL PSYCHIATRY. - 2158-3188. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.
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| 65. |
- Ramilowski, JA, et al.
(författare)
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Functional annotation of human long noncoding RNAs via molecular phenotyping
- 2020
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Ingår i: Genome research. - : Cold Spring Harbor Laboratory. - 1549-5469 .- 1088-9051. ; 30:7, s. 1060-1072
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Tidskriftsartikel (refereegranskat)abstract
- Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.
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| 66. |
- 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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| 67. |
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| 68. |
- Hashimoto, T., et al.
(författare)
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The MUSE Hubble Ultra Deep Field Survey X. Ly alpha equivalent widths at 2.9 < z < 6.6
- 2017
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 608
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Tidskriftsartikel (refereegranskat)abstract
- We present rest-frame Ly alpha equivalent widths (EW0) of 417 Ly alpha emitters (LAEs) detected with Multi Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope (VLT) at 2.9 < z < 6.6 in the Hubble Ultra Deep Field. Based on the deep MUSE spectroscopy and ancillary Hubble Space Telescope (HST) photometry data, we carefully measured EW0 values taking into account extended Ly alpha emission and UV continuum slopes (beta). Our LAEs reach unprecedented depths, both in Ly alpha luminosities and UV absolute magnitudes, from log (L-Ly alpha/erg s(-1)) similar to 41.0 to 43.0 and from M-UV similar to -16 to -21 (0.01-1.0 L-z=3(*)). The EW0 values span the range of similar to 5 to 240 angstrom or larger, and their distribution can be well fitted by an exponential law N = N-0 exp(-EW0/w(0)). Owing to the high dynamic range in M-UV, we find that the scale factor, w(0), depends on M-UV in the sense that including fainter M-UV objects increases w(0), i.e., the Ando effect. The results indicate that selection functions affect the EW0 scale factor. Taking these effects into account, we find that our w(0) values are consistent with those in the literature within 1 sigma uncertainties at 2.9 < z < 6.6 at a given threshold of M-UV and LLy alpha. Interestingly, we find 12 objects with EW0> 200 angstrom above 1 sigma uncertainties. Two of these 12 LAEs show signatures of merger or AGN activity: the weak Civ lambda 1549 emission line. For the remaining 10 very large EW0 LAEs, we find that the EW0 values can be reproduced by young stellar ages (< 100 Myr) and low metallicities (less than or similar to 0.02 Z(circle dot)). Otherwise, at least part of the Ly alpha emission in these LAEs needs to arise from anisotropic radiative transfer effects, fluorescence by hidden AGN or quasi-stellar object activity, or gravitational cooling.
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| 69. |
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| 70. |
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