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- Cluver, Catherine Anne, et al.
(author)
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Does metformin prolong pregnancy in preterm pre-eclampsia? A study protocol for a South African, hospital-based double-blind, randomised, placebo-controlled trial
- 2024
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In: BMJ OPEN. - 2044-6055. ; 14:6
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Journal article (peer-reviewed)abstract
- Introduction Preterm pre-eclampsia is a leading cause of maternal morbidity and mortality. The Pre-eclampsia Intervention 2 (PI 2) trial suggested that metformin sustained release (XR) may prolong gestation by a week in pregnant women undergoing expectant management (7.6days, geometric mean ratio 1.39, 95% CI 0.99 to 1.95; p=0.057). These findings should be confirmed with a larger sample size, and we need to know if such a prolongation improves neonatal outcome. Here, we describe the protocol for such a follow-up trial. Methods The PI 3 trial is a phase III, intention-to-treat, double-blind, placebo-controlled randomised clinical trial to assess if metformin XR can prolong gestation and improve neonatal outcomes in women undergoing expectant management for preterm pre-eclampsia. We will recruit women who are between 26+0and 31+6 weeks pregnant. Women will be randomised to receive either 3 g metformin XR or an identical placebo in divided daily doses. The primary outcome is prolongation of pregnancy. Secondary outcomes are neonatal birth weight and length of neonatal care admission (an indicator of neonatal health at birth). All other outcomes will be exploratory. We will record tolerability and adverse events. We plan a sample size of 500 participants to be powered for the primary and secondary outcomes. Ethics and dissemination PI 3 has ethical approval (Health Research Ethics Committee 2, Stellenbosch University, Protocol number M21/03/007, Project ID 21639, Federal Wide Assurance Number 00001372, Institutional Review Board Number IRB0005239), and is registered with the Pan African Clinical Trial Registry (PACTR202104532026017) and the South African Medicine Control Council (20211211). Data will be presented at international conferences and published in peer-reviewed journals. Trial registration number PACTR202104532026017)
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- Falster, Daniel, et al.
(author)
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AusTraits, a curated plant trait database for the Australian flora
- 2021
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In: Scientific Data. - : Nature Portfolio. - 2052-4463. ; 8:1
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Journal article (peer-reviewed)abstract
- We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.
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- Locke, Adam E, et al.
(author)
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Genetic studies of body mass index yield new insights for obesity biology.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
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Journal article (peer-reviewed)abstract
- Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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- Mahajan, Anubha, et al.
(author)
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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
- 2022
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:5, s. 560-572
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Journal article (peer-reviewed)abstract
- We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
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| 7. |
- Schweinsberg, Martin, et al.
(author)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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In: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Journal article (peer-reviewed)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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- Wuttke, Matthias, et al.
(author)
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A catalog of genetic loci associated with kidney function from analyses of a million individuals
- 2019
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In: Nature Genetics. - : NATURE PUBLISHING GROUP. - 1061-4036 .- 1546-1718. ; 51:6, s. 957-972
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Journal article (peer-reviewed)abstract
- Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.
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