| 1. |
- Dornelas, M., et al.
(author)
-
BioTIME: A database of biodiversity time series for the Anthropocene
- 2018
-
In: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 27:7, s. 760-786
-
Journal article (peer-reviewed)abstract
- Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
|
|
| 2. |
- Crous, P. W., et al.
(author)
-
Fungal Planet description sheets: 1478-1549
- 2023
-
In: Persoonia. - 0031-5850. ; 50, s. 158-310
-
Journal article (peer-reviewed)abstract
- Novel species of fungi described in this study include those from various countries as follows: Australia, Aschersonia mackerrasiae on whitefly, Cladosporium corticola on bark of Melaleuca quinquenervia, Penicillium nudgee from soil under Melaleuca quinquenervia, Pseudocercospora blackwoodiae on leaf spot of Persoonia fal- cata, and Pseudocercospora dalyelliae on leaf spot of Senna alata. Bolivia, Aspicilia lutzoniana on fully submersed siliceous schist in high-mountain streams, and Niesslia parviseta on the lower part and apothecial discs of Erioderma barbellatum on a twig. Brazil, Cyathus bonsai on decaying wood, Geastrum albofibrosum from moist soil with leaf litter, Laetiporus pratigiensis on a trunk of a living unknown hardwood tree species, and Scytalidium synnematicum on dead twigs of unidentified plant. Bulgaria, Amanita abscondita on sandy soil in a plantation of Quercus suber. Canada, Penicillium acericola on dead bark of Acer saccharum, and Penicillium corticola on dead bark of Acer saccharum. China, Colletotrichum qingyuanense on fruit lesion of Capsicum annuum. Denmark, Helminthosphaeria leptospora on corticioid Neohypochnicium cremicolor. Ecuador (Galapagos), Phaeosphaeria scalesiae on Scalesia sp. Finland, Inocybe jacobssonii on calcareous soils in dry forests and park habitats. France, Cortinarius rufomyr- rheus on sandy soil under Pinus pinaster, and Periconia neominutissima on leaves of Poaceae. India, Coprinopsis fragilis on decaying bark of logs, Filoboletus keralensis on unidentified woody substrate, Penicillium sankaranii from soil, Physisporinus tamilnaduensis on the trunk of Azadirachta indica, and Poronia nagaraholensis on elephant dung. Iran, Neosetophoma fici on infected leaves of Ficus elastica. Israel, Cnidariophoma eilatica (incl. Cnidario- phoma gen. nov.) from Stylophora pistillata. Italy, Lyophyllum obscurum on acidic soil. Namibia, Aureobasidium faidherbiae on dead leaf of Faidherbia albida, and Aureobasidium welwitschiae on dead leaves of Welwitschia mirabilis. Netherlands, Gaeumannomycella caricigena on dead culms of Carex elongata, Houtenomyces caricicola (incl. Houtenomyces gen. nov.) on culms of Carex disticha, Neodacampia ulmea (incl. Neodacampia gen. nov.) on branch of Ulmus laevis, Niesslia phragmiticola on dead standing culms of Phragmites australis, Pseudopyricularia caricicola on culms of Carex disticha, and Rhodoveronaea nieuwwulvenica on dead bamboo sticks. Norway, Arrhenia similis half-buried and moss-covered pieces of rotting wood in grass-grown path. Pakistan, Mallocybe ahmadii on soil. Poland, Beskidomyces laricis (incl. Beskidomyces gen. nov.) from resin of Larix decidua ssp. polonica, Lapi- domyces epipinicola from sooty mould community on Pinus nigra, and Leptographium granulatum from a gallery of Dendroctonus micans on Picea abies. Portugal, Geoglossum azoricum on mossy areas of laurel forest areas planted with Cryptomeria japonica, and Lunasporangiospora lusitanica from a biofilm covering a biodeteriorated limestone wall. Qatar, Alternaria halotolerans from hypersaline sea water, and Alternaria qatarensis from water sample collected from hypersaline lagoon. South Africa, Alfaria thamnochorti on culm of Thamnochortus fraternus, Knufia aloeicola on Aloe gariepensis, Muriseptatomyces restionacearum (incl. Muriseptatomyces gen. nov. ) on culms of Restionaceae, Neocladosporium arctotis on nest of cases of bag worm moths (Lepidoptera, Psychidae) on Arctotis auriculata, Neodevriesia scadoxi on leaves of Scadoxus puniceus, Paraloratospora schoenoplecti on stems of Schoenoplectus lacustris, Tulasnella epidendrea from the roots of Epidendrum x obrienianum, and Xenoidriella cinnamomi (incl. Xenoidriella gen. nov.) on leaf of Cinnamomum camphora. South Korea, Lemonniera fraxinea on decaying leaves of Fraxinus sp. from pond. Spain, Atheniella lauri on the bark of fallen trees of Laurus nobilis, Halocryptovalsa endophytica from surface-sterilised, asymptomatic roots of Salicornia patula, Inocybe amygda- liolens on soil in mixed forest, Inocybe pityusarum on calcareous soil in mixed forest, Inocybe roseobulbipes on acidic soils, Neonectria borealis from roots of Vitis berlandieri x Vitis rupestris, Sympoventuria eucalyptorum on leaves of Eucalyptus sp., and Tuber conchae from soil. Sweden, Inocybe bidumensis on calcareous soil. Thailand, Cordyceps sandindaengensis on Lepidoptera pupa, buried in soil, Ophiocordyceps kuchinaraiensis on Coleoptera larva, buried in soil, and Samsoniella winandae on Lepidoptera pupa, buried in soil. Taiwan region (China), Neo- phaeosphaeria livistonae on dead leaf of Livistona rotundifolia. Turkiye, Melanogaster anatolicus on clay loamy soils. UK, Basingstokeomyces allii (incl. Basingstokeomyces gen. nov.) on leaves of Allium schoenoprasum. Ukraine, Xenosphaeropsis corni on recently dead stem of Cornus alba. USA, Nothotrichosporon aquaticum (incl. Nothotrichosporon gen. nov.) from water, and Periconia philadelphiana from swab of coil surface. Morphological and culture characteristics for these new taxa are supported by DNA barcodes.
|
|
| 3. |
- Reinbold, C. S., et al.
(author)
-
Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder
- 2018
-
In: Frontiers in Psychiatry. - : Frontiers Media SA. - 1664-0640. ; 9
-
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.
|
|
| 4. |
- Amare, A. T., et al.
(author)
-
Association of polygenic score for major depression with response to lithium in patients with bipolar disorder
- 2021
-
In: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 2457-2470
-
Journal article (peer-reviewed)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.
|
|
| 5. |
- Cearns, M., et al.
(author)
-
Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- 2022
-
In: British Journal of Psychiatry. - : Royal College of Psychiatrists. - 0007-1250 .- 1472-1465. ; 220:4, s. 219-228
-
Journal article (peer-reviewed)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.
|
|
| 6. |
- Le Clerc, S., et al.
(author)
-
HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders
- 2021
-
In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1
-
Journal article (peer-reviewed)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.
|
|
| 7. |
- Schubert, K. O., et al.
(author)
-
Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients
- 2021
-
In: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 11:1
-
Journal article (peer-reviewed)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.
|
|
| 8. |
- van Dissel, A. C., et al.
(author)
-
End-stage heart failure in congenitally corrected transposition of the great arteries: a multicentre study
- 2023
-
In: European Heart Journal. - 0195-668X. ; 44:34, s. 3278-3291
-
Journal article (peer-reviewed)abstract
- Background and Aims For patients with congenitally corrected transposition of the great arteries (ccTGA), factors associated with progression to end-stage congestive heart failure (CHF) remain largely unclear. Methods This multicentre, retrospective cohort study included adults with ccTGA seen at a congenital heart disease centre. Clinical data from initial and most recent visits were obtained. The composite primary outcome was mechanical circulatory support, heart transplantation, or death. Results From 558 patients (48% female, age at first visit 36 & PLUSMN; 14.2 years, median follow-up 8.7 years), the event rate of the primary outcome was 15.4 per 1000 person-years (11 mechanical circulatory support implantations, 12 transplantations, and 52 deaths). Patients experiencing the primary outcome were older and more likely to have a history of atrial arrhythmia. The primary outcome was highest in those with both moderate/severe right ventricular (RV) dysfunction and tricuspid regurgitation (n = 110, 31 events) and uncommon in those with mild/less RV dysfunction and tricuspid regurgitation (n = 181, 13 events, P < .001). Outcomes were not different based on anatomic complexity and history of tricuspid valve surgery or of subpulmonic obstruction. New CHF admission or ventricular arrhythmia was associated with the primary outcome. Individuals who underwent childhood surgery had more adverse outcomes than age- and sex-matched controls. Multivariable Cox regression analysis identified older age, prior CHF admission, and severe RV dysfunction as independent predictors for the primary outcome. Conclusions Patients with ccTGA have variable deterioration to end-stage heart failure or death over time, commonly between their fifth and sixth decades. Predictors include arrhythmic and CHF events and severe RV dysfunction but not anatomy or need for tricuspid valve surgery.
|
|
| 9. |
- Broberg, C. S., et al.
(author)
-
Long-Term Outcomes After Atrial Switch Operation for Transposition of the Great Arteries
- 2022
-
In: Journal of the American College of Cardiology. - : Elsevier BV. - 0735-1097. ; 80:10, s. 951-963
-
Journal article (peer-reviewed)abstract
- Background: For patients with d-loop transposition of the great arteries (d-TGA) with a systemic right ventricle after an atrial switch operation, there is a need to identify risks for end-stage heart failure outcomes. Objectives: The authors aimed to determine factors associated with survival in a large cohort of such individuals. Methods: This multicenter, retrospective cohort study included adults with d-TGA and prior atrial switch surgery seen at a congenital heart center. Clinical data from initial and most recent visits were obtained. The composite primary outcome was death, transplantation, or mechanical circulatory support (MCS). Results: From 1,168 patients (38% female, age at first visit 29 ± 7.2 years) during a median 9.2 years of follow-up, 91 (8.8% per 10 person-years) met the outcome (66 deaths, 19 transplantations, 6 MCS). Patients experiencing sudden/arrhythmic death were younger than those dying of other causes (32.6 ± 6.4 years vs 42.4 ± 6.8 years; P < 0.001). There was a long duration between sentinel clinical events and end-stage heart failure. Age, atrial arrhythmia, pacemaker, biventricular enlargement, systolic dysfunction, and tricuspid regurgitation were all associated with the primary outcome. Independent 5-year predictors of primary outcome were prior ventricular arrhythmia, heart failure admission, complex anatomy, QRS duration >120 ms, and severe right ventricle dysfunction based on echocardiography. Conclusions: For most adults with d-TGA after atrial switch, progress to end-stage heart failure or death is slow. A simplified prediction score for 5-year adverse outcome is derived to help identify those at greatest risk.
|
|
| 10. |
|
|
