| 1. |
- Smith, Jennifer A, et al.
(author)
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Genome-wide association study identifies 74 loci associated with educational attainment
- 2016
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In: Nature (London). - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 533:7604, s. 539-542
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Journal article (peer-reviewed)abstract
- Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
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| 2. |
- Sherratt, K., et al.
(author)
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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
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In: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
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Journal article (peer-reviewed)abstract
- Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
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| 3. |
- Melsen, Wilhelmina G., et al.
(author)
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Attributable mortality of ventilator-associated pneumonia: a meta-analysis of individual patient data from randomised prevention studies
- 2013
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In: The Lancet. Infectious Diseases. - 1474-4457. ; 13:8, s. 665-671
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Journal article (peer-reviewed)abstract
- Background Estimating attributable mortality of ventilator-associated pneumonia has been hampered by confounding factors, small sample sizes, and the difficulty of doing relevant subgroup analyses. We estimated the attributable mortality using the individual original patient data of published randomised trials of ventilator-associated pneumonia prevention. Methods We identified relevant studies through systematic review. We analysed individual patient data in a one-stage meta-analytical approach (in which we defined attributable mortality as the ratio between the relative risk reductions [RRR] of mortality and ventilator-associated pneumonia) and in competing risk analyses. Predefined subgroups included surgical, trauma, and medical patients, and patients with different categories of severity of illness scores. Findings Individual patient data were available for 6284 patients from 24 trials. The overall attributable mortality was 13%, with higher mortality rates in surgical patients and patients with mid-range severity scores at admission (ie, acute physiology and chronic health evaluation score [APACHE] 20-29 and simplified acute physiology score [SAPS 2] 35-58). Attributable mortality was close to zero in trauma, medical patients, and patients with low or high severity of illness scores. Competing risk analyses could be done for 5162 patients from 19 studies, and the overall daily hazard for intensive care unit (ICU) mortality after ventilator-associated pneumonia was 1.13 (95% CI 0.98-1.31). The overall daily risk of discharge after ventilator-associated pneumonia was 0.74 (0-68-0.80), leading to an overall cumulative risk for dying in the ICU of 2.20 (1.91-2.54). Highest cumulative risks for dying from ventilator-associated pneumonia were noted for surgical patients (2.97,95% CI 2-24-3-94) and patients with mid-range severity scores at admission (ie, cumulative risks of 2.49 [1.81-3-44] for patients with APACHE scores of 20-29 and 2.72 [1.95-3.78] for those with SAPS 2 scores of 35-58). Interpretation The overall attributable mortality of ventilator-associated pneumonia is 13%, with higher rates for surgical patients and patients with a mid-range severity score at admission. Attributable mortality is mainly caused by prolonged exposure to the risk of dying due to increased length of ICU stay.
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| 4. |
- Dand, Nick, et al.
(author)
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Exome-wide association study reveals novel psoriasis susceptibility locus at TNFSF15 and rare protective alleles in genes contributing to type I IFN signalling
- 2017
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In: Human Molecular Genetics. - : OXFORD UNIV PRESS. - 0964-6906 .- 1460-2083. ; 26:21, s. 4301-4313
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Journal article (peer-reviewed)abstract
- Psoriasis is a common inflammatory skin disorder for which multiple genetic susceptibility loci have been identified, but few resolved to specific functional variants. In this study, we sought to identify common and rare psoriasis-associated gene-centric variation. Using exome arrays we genotyped four independent cohorts, totalling 11 861 psoriasis cases and 28 610 controls, aggregating the dataset through statistical meta-analysis. Single variant analysis detected a previously unreported risk locus at TNFSF15 (rs6478108; P = 1.50 x 10(-8), OR = 1.10), and association of common protein-altering variants at 11 loci previously implicated in psoriasis susceptibility. We validate previous reports of protective low-frequency protein-altering variants within IFIH1 (encoding an innate antiviral receptor) and TYK2 (encoding a Janus kinase), in each case establishing a further series of protective rare variants (minor allele frequency amp;lt; 0.01) via gene-wide aggregation testing (IFIH1: p(burden) = 2.53 x 10(-7), OR = 0.707; TYK2: p(burden) = 6.17 x 10(-4), OR = 0.744). Both genes play significant roles in type I interferon (IFN) production and signalling. Several of the protective rare and low-frequency variants in IFIH1 and TYK2 disrupt conserved protein domains, highlighting potential mechanisms through which their effect may be exerted.
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