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- Ruilope, LM, et al.
(författare)
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Design and Baseline Characteristics of the Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease Trial
- 2019
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Ingår i: American journal of nephrology. - : S. Karger AG. - 1421-9670 .- 0250-8095. ; 50:5, s. 345-356
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Tidskriftsartikel (refereegranskat)abstract
- <b><i>Background:</i></b> Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. <b><i>Patients and</i></b> <b><i>Methods:</i></b> The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate ≥25 mL/min/1.73 m<sup>2</sup> and albuminuria (urinary albumin-to-creatinine ratio ≥30 to ≤5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level α = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. <b><i>Conclusions:</i></b> FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049.
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| 2. |
- Mullins, N., et al.
(författare)
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Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
- 2021
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 53, s. 817-829
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.
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| 3. |
- Abrams, M. B., et al.
(författare)
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A Standards Organization for Open and FAIR Neuroscience : the International Neuroinformatics Coordinating Facility
- 2021
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Ingår i: Neuroinformatics. - : Springer Nature. - 1539-2791 .- 1559-0089.
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Tidskriftsartikel (refereegranskat)abstract
- There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.
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| 5. |
- Chatzidionysiou, K., et al.
(författare)
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Effectiveness of a Second Biologic After Failure of a Non-tumor Necrosis Factor Inhibitor As First Biologic in Rheumatoid Arthritis
- 2021
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Ingår i: Journal of Rheumatology. - : The Journal of Rheumatology. - 0315-162X .- 1499-2752. ; 48:10, s. 1512-1518
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Tidskriftsartikel (refereegranskat)abstract
- Objective. In rheumatoid arthritis (RA), evidence regarding the effectiveness of a second biologic disease-modifying antirheumatic drug (bDMARD) in patients whose first-ever bDMARD was a non-tumor necrosis factor inhibitor (TNFi) bDMARD is limited. The objective of this study was therefore to assess the outcome of a second bDMARD (non-TNFi: rituximab [RTX], abatacept [ABA], or tocilizumab [TCZ], separately; and TNFi) after failure of a non-TNFi bDMARD as first bDMARD. Methods. We identified patients with RA from the 5 Nordic biologics registers who started treatment with a non-TNFi as first-ever bDMARD but switched to a second bDMARD. For the second bDMARD, we assessed drug survival (at 6 and 12 months) and primary response (at 6 months). Results. We included 620 patients starting a second bDMARD (ABA 86, RTX 40, TCZ 67, and TNFi 427) following failure of a first non-TNFi bDMARD. At 6 and 12 months after start of their second bDMARD, approximately 70% and 60%, respectively, remained on treatment, and at 6 months, less than one-third of patients were still on their second bDMARD and had reached low disease activity or remission according to the Disease Activity Score in 28 joints. For those patients whose second bMDARD was a TNFi, the corresponding proportion was slightly higher (40%). Conclusion. The drug survival and primary response of a second bDMARD in patients with RA switching due to failure of a non-TNFi bDMARD as first bDMARD is modest. Some patients may benefit from TNFi when used after failure of a non-TNFi as first bDMARD.
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| 8. |
- Fecchio, Alan, et al.
(författare)
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Global drivers of avian haemosporidian infections vary across zoogeographical regions
- 2021
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Ingår i: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 30:12, s. 2393-2406
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Macroecological analyses provide valuable insights into factors that influence how parasites are distributed across space and among hosts. Amid large uncertainties that arise when generalizing from local and regional findings, hierarchical approaches applied to global datasets are required to determine whether drivers of parasite infection patterns vary across scales. We assessed global patterns of haemosporidian infections across a broad diversity of avian host clades and zoogeographical realms to depict hotspots of prevalence and to identify possible underlying drivers. Location: Global. Time period: 1994–2019. Major taxa studied: Avian haemosporidian parasites (genera Plasmodium, Haemoproteus, Leucocytozoon and Parahaemoproteus). Methods: We amalgamated infection data from 53,669 individual birds representing 2,445 species world-wide. Spatio-phylogenetic hierarchical Bayesian models were built to disentangle potential landscape, climatic and biotic drivers of infection probability while accounting for spatial context and avian host phylogenetic relationships. Results: Idiosyncratic responses of the three most common haemosporidian genera to climate, habitat, host relatedness and host ecological traits indicated marked variation in host infection rates from local to global scales. Notably, host ecological drivers, such as migration distance for Plasmodium and Parahaemoproteus, exhibited predominantly varying or even opposite effects on infection rates across regions, whereas climatic effects on infection rates were more consistent across realms. Moreover, infections in some low-prevalence realms were disproportionately concentrated in a few local hotspots, suggesting that regional-scale variation in habitat and microclimate might influence transmission, in addition to global drivers. Main conclusions: Our hierarchical global analysis supports regional-scale findings showing the synergistic effects of landscape, climate and host ecological traits on parasite transmission for a cosmopolitan and diverse group of avian parasites. Our results underscore the need to account for such interactions, in addition to possible variation in drivers across regions, to produce the robust inference required to predict changes in infection risk under future scenarios.
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