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- Gorski, Mathias, et al.
(författare)
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Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies
- 2022
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Ingår i: Kidney International. - : Elsevier. - 0085-2538 .- 1523-1755. ; 102:3, s. 624-639
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Tidskriftsartikel (refereegranskat)abstract
- Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genomewide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR- baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant- by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with agedependency of genetic cross- section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in- silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03- 1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.
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- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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3. |
- Meisl, Christina J., et al.
(författare)
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Nomograms including the UBC (R) Rapid test to detect primary bladder cancer based on a multicentre dataset
- 2022
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Ingår i: BJU International. - : John Wiley & Sons. - 1464-4096 .- 1464-410X. ; 130:6, s. 754-763
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Tidskriftsartikel (refereegranskat)abstract
- Objectives To evaluate the clinical utility of the urinary bladder cancer antigen test UBC (R) Rapid for the diagnosis of bladder cancer (BC) and to develop and validate nomograms to identify patients at high risk of primary BC. Patients and Methods Data from 1787 patients from 13 participating centres, who were tested between 2012 and 2020, including 763 patients with BC, were analysed. Urine samples were analysed with the UBC (R) Rapid test. The nomograms were developed using data from 320 patients and externally validated using data from 274 patients. The diagnostic accuracy of the UBC (R) Rapid test was evaluated using receiver-operating characteristic curve analysis. Brier scores and calibration curves were chosen for the validation. Biopsy-proven BC was predicted using multivariate logistic regression. Results The sensitivity, specificity, and area under the curve for the UBC (R) Rapid test were 46.4%, 75.5% and 0.61 (95% confidence interval [CI] 0.58-0.64) for low-grade (LG) BC, and 70.5%, 75.5% and 0.73 (95% CI 0.70-0.76) for high-grade (HG) BC, respectively. Age, UBC (R) Rapid test results, smoking status and haematuria were identified as independent predictors of primary BC. After external validation, nomograms based on these predictors resulted in areas under the curve of 0.79 (95% CI 0.72-0.87) and 0.95 (95% CI: 0.92-0.98) for predicting LG-BC and HG-BC, respectively, showing excellent calibration associated with a higher net benefit than the UBC (R) Rapid test alone for low and medium risk levels in decision curve analysis. The R Shiny app allows the results to be explored interactively and can be accessed at www.blucab-index. net. Conclusion The UBC (R) Rapid test alone has limited clinical utility for predicting the presence of BC. However, its combined use with BC risk factors including age, smoking status and haematuria provides a fast, highly accurate and non-invasive tool for screening patients for primary LG-BC and especially primary HG-BC.
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