| 1. |
- Kato, Norihiro, et al.
(författare)
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Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation
- 2015
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 47:11, s. 1282-1293
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Tidskriftsartikel (refereegranskat)abstract
- We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10−11 to 5.0 × 10−21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10−6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.
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| 2. |
- Haiman, Christopher A., et al.
(författare)
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A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor-negative breast cancer
- 2011
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 43:12, s. 61-1210
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Tidskriftsartikel (refereegranskat)abstract
- Estrogen receptor (ER)-negative breast cancer shows a higher incidence in women of African ancestry compared to women of European ancestry. In search of common risk alleles for ER-negative breast cancer, we combined genome-wide association study (GWAS) data from women of African ancestry (1,004 ER-negative cases and 2,745 controls) and European ancestry (1,718 ER-negative cases and 3,670 controls), with replication testing conducted in an additional 2,292 ER-negative cases and 16,901 controls of European ancestry. We identified a common risk variant for ER-negative breast cancer at the TERT-CLPTM1L locus on chromosome 5p15 (rs10069690: per-allele odds ratio (OR) = 1.18 per allele, P = 1.0 x 10(-10)). The variant was also significantly associated with triple-negative (ER-negative, progesterone receptor (PR)-negative and human epidermal growth factor-2 (HER2)-negative) breast cancer (OR = 1.25, P = 1.1 x 10(-9)), particularly in younger women (<50 years of age) (OR = 1.48, P = 1.9 x 10(-9)). Our results identify a genetic locus associated with estrogen receptor negative breast cancer subtypes in multiple populations.
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| 3. |
- White, Christopher J., et al.
(författare)
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Potential applications of subseasonal-to-seasonal (S2S) predictions
- 2017
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Ingår i: Meteorological Applications. - : John Wiley & Sons. - 1350-4827 .- 1469-8080. ; 24:3, s. 315-325
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Tidskriftsartikel (refereegranskat)abstract
- While seasonal outlooks have been operational for many years, until recently the extended-range timescale referred to as subseasonal-to-seasonal (S2S) has received little attention. S2S prediction fills the gap between short-range weather prediction and long-range seasonal outlooks. Decisions in a range of sectors are made in this extended-range lead time; therefore, there is a strong demand for this new generation of forecasts. International efforts are under way to identify key sources of predictability, improve forecast skill and operationalize aspects of S2S forecasts; however, challenges remain in advancing this new frontier. If S2S predictions are to be used effectively, it is important that, along with science advances, an effort is made to develop, communicate and apply these forecasts appropriately. In this study, the emerging operational S2S forecasts are presented to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. The value of applications-relevant S2S predictions is explored, and the opportunities and challenges facing their uptake are highlighted. It is shown how social sciences can be integrated with S2S development, from communication to decision-making and valuation of forecasts, to enhance the benefits of ‘climate services’ approaches for extended-range forecasting. While S2S forecasting is at a relatively early stage of development, it is concluded that it presents a significant new window of opportunity that can be explored for application-ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon.
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| 4. |
- Tustison, Nicholas J., et al.
(författare)
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The ANTsX ecosystem for quantitative biological and medical imaging
- 2021
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1, s. 9068-9068
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Tidskriftsartikel (refereegranskat)abstract
- The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis.
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| 5. |
- Ahmed, Fozia Z., et al.
(författare)
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Use of healthcare claims to validate the Prevention of Arrhythmia Device Infection Trial cardiac implantable electronic device infection risk score
- 2021
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Ingår i: Europace. - : Oxford University Press. - 1099-5129 .- 1532-2092. ; 23:9, s. 1446-1455
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Tidskriftsartikel (refereegranskat)abstract
- AIM: The Prevention of Arrhythmia Device Infection Trial (PADIT) infection risk score, developed based on a large prospectively collected data set, identified five independent predictors of cardiac implantable electronic device (CIED) infection. We performed an independent validation of the risk score in a data set extracted from U.S. healthcare claims.METHODS AND RESULTS: Retrospective identification of index CIED procedures among patients aged ≥18 years with at least one record of a CIED procedure between January 2011 and September 2014 in a U.S health claims database. PADIT risk factors and major CIED infections (with system removal, invasive procedure without system removal, or infection-attributable death) were identified through diagnosis and procedure codes. The data set was randomized by PADIT score into Data Set A (60%) and Data Set B (40%). A frailty model allowing multiple procedures per patient was fit using Data Set A, with PADIT score as the only predictor, excluding patients with prior CIED infection. A data set of 54 042 index procedures among 51 623 patients with 574 infections was extracted. Among patients with no history of prior CIED infection, a 1 unit increase in the PADIT score was associated with a relative 28% increase in infection risk. Prior CIED infection was associated with significant incremental predictive value (HR 5.66, P < 0.0001) after adjusting for PADIT score. A Harrell's C-statistic for the PADIT score and history of prior CIED infection was 0.76.CONCLUSION: The PADIT risk score predicts increased CIED infection risk, identifying higher risk patients that could potentially benefit from targeted interventions to reduce the risk of CIED infection. Prior CIED infection confers incremental predictive value to the PADIT score.
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