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- de Rojas, I., et al.
(författare)
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Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores
- 2021
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease. © 2021, The Author(s).
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- Pierre, M., et al.
(författare)
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The XXL survey : First results and future
- 2017
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Ingår i: Astronomical Notes - Astronomische Nachrichten. - : Wiley-VCH Verlagsgesellschaft. - 0004-6337 .- 1521-3994. ; 338:2-3, s. 334-341
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Tidskriftsartikel (refereegranskat)abstract
- The XXL survey currently covers two 25 deg(2) patches with XMM observations of similar to 10 ks. We summarize the scientific results associated with the first release of the XXL dataset, which occurred in mid-2016. We review several arguments for increasing the survey depth to 40 ks during the next decade of XMM operations. X-ray (z < 2) cluster, (z < 4) active galactic nuclei (AGN), and cosmic background survey science will then benefit from an extraordinary data reservoir. This, combined with deep multi-lambda observations, will lead to solid standalone cosmological constraints and provide a wealth of information on the formation and evolution of AGN, clusters, and the X-ray background. In particular, it will offer a unique opportunity to pinpoint the z > 1 cluster density. It will eventually constitute a reference study and an ideal calibration field for the upcoming eROSITA and Euclid missions.
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- Pierre, M., et al.
(författare)
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The XXL Survey I. Scientific motivations - XMM-Newton observing plan - Follow-up observations and simulation programme
- 2016
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 592
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Tidskriftsartikel (refereegranskat)abstract
- Context. The quest for the cosmological parameters that describe our universe continues to motivate the scientific community to undertake very large survey initiatives across the electromagnetic spectrum. Over the past two decades, the Chandra and XMM-Newton observatories have supported numerous studies of X-ray-selected clusters of galaxies, active galactic nuclei (AGNs), and the X-ray background. The present paper is the first in a series reporting results of the XXL-XMM survey; it comes at a time when the Planck mission results are being finalised. Aims. We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms to date and involving an international consortium of roughly 100 members. The XXL Survey covers two extragalactic areas of 25 deg(2) each at a point-source sensitivity of similar to 5 x 10(-15) erg s(-1) cm(-2) in the [0.5-2] keV band (completeness limit). The survey's main goals are to provide constraints on the dark energy equation of state from the space-time distribution of clusters of galaxies and to serve as a pathfinder for future, wide-area X-ray missions. We review science objectives, including cluster studies, AGN evolution, and large-scale structure, that are being conducted with the support of approximately 30 follow-up programmes. Methods. We describe the 542 XMM observations along with the associated multi-lambda and numerical simulation programmes. We give a detailed account of the X-ray processing steps and describe innovative tools being developed for the cosmological analysis. Results. The paper provides a thorough evaluation of the X-ray data, including quality controls, photon statistics, exposure and background maps, and sky coverage. Source catalogue construction and multi-lambda associations are briefly described. This material will be the basis for the calculation of the cluster and AGN selection functions, critical elements of the cosmological and science analyses. Conclusions. The XXL multi-lambda data set will have a unique lasting legacy value for cosmological and extragalactic studies and will serve as a calibration resource for future dark energy studies with clusters and other X-ray selected sources. With the present article, we release the XMM XXL photon and smoothed images along with the corresponding exposure maps.
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- Bonham, LW, et al.
(författare)
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Genetic variation across RNA metabolism and cell death gene networks is implicated in the semantic variant of primary progressive aphasia
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10854-
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Tidskriftsartikel (refereegranskat)abstract
- The semantic variant of primary progressive aphasia (svPPA) is a clinical syndrome characterized by neurodegeneration and progressive loss of semantic knowledge. Unlike many other forms of frontotemporal lobar degeneration (FTLD), svPPA has a highly consistent underlying pathology composed of TDP-43 (a regulator of RNA and DNA transcription metabolism). Previous genetic studies of svPPA are limited by small sample sizes and a paucity of common risk variants. Despite this, svPPA’s relatively homogenous clinicopathologic phenotype makes it an ideal investigative model to examine genetic processes that may drive neurodegenerative disease. In this study, we used GWAS metadata, tissue samples from pathologically confirmed frontotemporal lobar degeneration, and in silico techniques to identify and characterize protein interaction networks associated with svPPA risk. We identified 64 svPPA risk genes that interact at the protein level. The protein pathways represented in this svPPA gene network are critical regulators of RNA metabolism and cell death, such as SMAD proteins and NOTCH1. Many of the genes in this network are involved in TDP-43 metabolism. Contrary to the conventional notion that svPPA is a clinical syndrome with few genetic risk factors, our analyses show that svPPA risk is complex and polygenic in nature. Risk for svPPA is likely driven by multiple common variants in genes interacting with TDP-43, along with cell death,x` working in combination to promote neurodegeneration.
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