| 11. |
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| 12. |
- Kanoni, Stavroula, et al.
(författare)
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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
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Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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| 13. |
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| 14. |
- Ramdas, S., et al.
(författare)
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A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
- 2022
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 109:8, s. 1366-1387
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Tidskriftsartikel (refereegranskat)abstract
- A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
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| 17. |
- Baby, Sultana Nasrin, et al.
(författare)
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Developing a Spatial Tool for Assessing Coastal Community and Identifying Infrastructure at Risk
- 2021
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Ingår i: Engineering. - China : Scientific Research Publishing Inc. - 1947-3931 .- 1947-394X. ; 13:1, s. 45-55
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Tidskriftsartikel (refereegranskat)abstract
- A recent trend of sea level shows constant rising. Sea level rise has caused asignificant risk to seaside areas. This study examines the potential effect ofclimate change and rising sea levels on coastal regions and evaluates the susceptibilityof coastal areas in Inverloch, Melbourne Australia. A model ofHypothetically Flooded Zones, based on LiDAR data was built, processed andmanipulated in ArcGIS. Through applying this model, the effect of rising sealevel on the infrastructures such as buildings, dwellings, roads, land use andthe population was assessed. Elevation data sets of varying resolution and accuracyhave been processed to show the improved quality of LiDAR datacontributes to a more precise delineation of flood-prone coastal lands. Afterthe susceptible areas to sea level rise were delineated, the worst-case scenariowas calculated (based on the increase in sea level projected for 2100) and itwould impacts about 0.86% of roads, 221 of different building infrastructures.This method can be used in other areas to protect the coasts due to rapidchanges caused by climate change.
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| 18. |
- Baby, Sultana Nasrin, et al.
(författare)
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Finding Areas at Risk from Floods in a Downpour Using the Lidar-Based Elevation Model
- 2021
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Ingår i: Journal of Civil Engineering and Architecture. - USA : David Publishing Company. - 1934-7359 .- 1934-7367. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- Climate change can impact coastal areas in different ways, including flooding, storm surges, and beach erosion. Of these, flooding has a major impact on the operation of coastal drainage systems. This paper develops a new flood screening model using a LiDAR based digital elevation model (DEM) to improve the implementation of Victorian’s coastal flooding risk assessment and management. Hydrological elevation models are directed towards protection from cloudbursts and applied to rising sea level. The aim is to simulate water flow on the ground and in streams, and the resulting accumulation of water in depressions of the blue spot using DEM. Due to the presence of pipes, watercourses, bridges and channels it was required that the DEM data to be lowered. The reservoirs of rain will prevent seawater from flowing across the stream channel into land. The rain drain will be open during normal sea levels to allow rain water in the river to move and flow in to the sea. Traditionally, geographic information system (GIS) assists with spatial data management, but lacks modelling capability for complex hydrology problems and cannot be relied upon by decision-makers in this sector. Functionality improvements are therefore required to improve the processing or analytical capabilities of GIS in hydrology. This research shows how the spatial data can be primarily processed by GIS adopting the spatial analysis routines associated with hydrology. The objective of this paper is to outline the importance of GIS technology for coastal flood management. Following a definition of the coastal flood, and, short description of its peculiarities and the urgency of its management, this paper describes the use of GIS technology in coastal flood management, its advantages and the consideration for accuracy. This is followed by the information and LiDAR data required for coastal flood management and the application area in coastal flood management. This paper method is presented to conduct a first high-resolution DEM screening to detect the degree and capacities of the sinks in the coastal landscape. When their capacities are established, the rain volumes received during a rainstorm from their coastal catchments are saved as attributes to the pour points. The conclusion emphases the importance of a geographical information system in coastal flood management for efficient data handling and analysis of geographically related data. Local governments at risk of coastal flooding that use the flood screening model can use to determine appropriate land use controls to manage long-term flood risk to human settlements.
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| 19. |
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| 20. |
- Conti, David, V, et al.
(författare)
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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- 2021
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:1, s. 65-75
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Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction. A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.
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