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A catalog of genetic loci associated with kidney function from analyses of a million individuals
(2019)
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.
Advances in biotechnologies rapidly increase the number of molecules of a cell which can be observed simultaneously. This includes expression levels of thousands or ten-thousands of genes as well as concentration levels of metabolites or proteins. Such Profile data, observed at different times or at different experimental conditions (e.g., heat or dry stress), show how the biological experiment is reflected on the molecular level. This information is helpful to understand the molecular behaviour and to identify molecules or combination of molecules that characterise specific biological condition (e.g., disease). This work shows the potentials of component extraction algorithms to identify the major factors which influenced the observed data. This can be the expected experimental factors such as the time or temperature as well as unexpected factors such as technical artefacts or even unknown biological behaviour. Extracting components means to reduce the very high-dimensional data to a small set of new variables termed components. Each component is a combination of all original variables. The classical approach for that purpose is the principal component analysis (PCA). It is shown that, in contrast to PCA which maximises the variance only, modern approaches such as independent component analysis (ICA) are more suitable for analysing molecular data. The condition of independence between components of ICA fits more naturally our assumption of individual (independent) factors which influence the data. This higher potential of ICA is demonstrated by a crossing experiment of the model plant Arabidopsis thaliana (Thale Cress). The experimental factors could be well identified and, in addition, ICA could even detect a technical artefact. However, in continuously observations such as in time experiments, the data show, in general, a nonlinear distribution. To analyse such nonlinear data, a nonlinear extension of PCA is used. This nonlinear PCA (NLPCA) is based on a neural network algorithm. The algorithm is adapted to be applicable to incomplete molecular data sets. Thus, it provides also the ability to estimate the missing data. The potential of nonlinear PCA to identify nonlinear factors is demonstrated by a cold stress experiment of Arabidopsis thaliana. The results of component analysis can be used to build a molecular network model. Since it includes functional dependencies it is termed functional network. Applied to the cold stress data, it is shown that functional networks are appropriate to visualise biological processes and thereby reveals molecular dynamics.
Bildung:digital
(2024)
Heute Morgen schon im Bett geswiped, geliked oder gepostet? Auf Arbeit an einer Video-Konferenz teilgenommen, eine Datenbank benutzt oder programmiert? Auf dem Heimweg schnell noch im Laden mit dem Smartphone bezahlt, Podcasts gehört und die Ausleihe der Bibliotheksbücher verlängert? Und abends auf der Couch mit dem Tablet auf ELSTER.de die Steuererklärung ausgefüllt, online geshoppt oder Rechnungen bezahlt, ehe die Streaming-Plattform mit einer Serie lockt?
Unser Leben ist durch und durch digitalisiert. Diese Veränderungen machen vieles schneller, leichter, effizienter. Doch damit Schritt zu halten, verlangt uns einiges ab und gelingt beileibe nicht allen. Es gibt Menschen, die für eine Überweisung lieber zur Bank gehen, das Programmieren den Experten überlassen, die Steuererklärung per Post schicken und das Smartphone nur zum Telefonieren benutzen. Sie wollen nicht, vielleicht können sie auch nicht. Haben es nicht gelernt. Andere, jüngere Menschen, wachsen als „Digital Natives“ inmitten digitaler Geräte, Tools und Prozesse auf. Aber können sie deshalb wirklich damit umgehen? Oder brauchen auch sie digitale Bildung?
Aber wie sieht erfolgreiche digitale Bildung eigentlich aus? Lernen wir dabei ein Tablet zu bedienen, richtig zu googeln und Excel-Tabellen zu schreiben? Möglicherweise geht es um mehr: darum, den umfassenden Wandel zu verstehen, der unsere Welt erfasst, seitdem sie in Einsen und Nullen zerlegt und virtuell neu aufgebaut wird. Aber wie lernen wir, in einer Welt der Digitalität zu leben – mit allem, was dazu gehört und zu unserem Nutzen? Für die aktuelle Ausgabe der „Portal Wissen“ haben wir uns an der Universität Potsdam umgeschaut, welche Rolle die Verbindung von Digitalisierung und Lernen in der Forschung der verschiedenen Disziplinen spielt: Wir haben mit Katharina Scheiter, Professorin für digitale Bildung, über die Zukunft in deutschen Schulen gesprochen und uns gleich von mehreren Expert*innen Beispiele dafür zeigen lassen, wie digitale Instrumente schulisches Lernen, aber auch Weiterbildung im Berufsleben verbessern können. Außerdem haben uns Forschende aus Informatik und Agrarforschung vorgeführt, wie auch gestandene Landwirte dank digitaler Hilfsmittel noch viel über ihr Land und ihre Arbeit lernen können. Wir haben mit Bildungsforschenden gesprochen, die mithilfe von Big Data analysieren, wie Jungen und Mädchen lernen und wo mögliche Ursachen für Unterschiede zu suchen sind. Die Bildungsund Politikwissenschaftlerin Nina Kolleck wiederum schaut auf Bildung vor dem Hintergrund der Globalisierung und setzt dabei auf die Auswertung von großen Mengen Social-Media- Daten.
Dabei verlieren wir natürlich die Vielfalt der Forschung an der Uni Potsdam nicht aus den Augen: Wir stellen der Strafrechtlerin Anna Albrecht 33 Fragen, begleiten eine Gruppe von Geoforschenden in den Himalaya und lassen uns erklären, welche Alternativen es bald zu Antibiotika geben könnte. Außerdem geht es in diesem Magazin um Stress und wie er uns krankmacht, die Forschung zu nachhaltiger Erzgewinnung und neue Ansätze in der Schulentwicklung.
Neu ist auch eine ganze Reihe kürzerer Beiträge, die zum Blättern und Schmökern einladen: von Forschungsnews und Personalia- Infos über fotografische Einblicke in Labore, einfache Erklärungen komplexer Phänomene und Ausblicke in die weite Forschungswelt bis hin zu einer kleinen Wissenschaftsutopie, einem persönlichen Dank an die Forschung und einem Wissenschaftscomic. All das im Namen der Bildung, versteht sich. Viel Vergnügen bei der Lektüre!
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Heterosis-associated cellular and molecular processes were analyzed in seeds and seedlings of Arabidopsis thaliana accessions Col-0 and C24 and their heterotic hybrids. Microscopic examination revealed no advantages in terms of hybrid mature embryo organ sizes or cell numbers. Increased cotyledon sizes were detectable 4 days after sowing. Growth heterosis results from elevated cell sizes and numbers, and is well established at 10 days after sowing. The relative growth rates of hybrid seedlings were most enhanced between 3 and 4 days after sowing. Global metabolite profiling and targeted fatty acid analysis revealed maternal inheritance patterns for a large proportion of metabolites in the very early stages. During developmental progression, the distribution shifts to dominant, intermediate and heterotic patterns, with most changes occurring between 4 and 6 days after sowing. The highest incidence of heterotic patterns coincides with establishment of size differences at 4 days after sowing. In contrast, overall transcript patterns at 4, 6 and 10 days after sowing are characterized by intermediate to dominant patterns, with parental transcript levels showing the largest differences. Overall, the results suggest that, during early developmental stages, intermediate gene expression and higher metabolic activity in the hybrids compared to the parents lead to better resource efficiency, and therefore enhanced performance in the hybrids.
HPI Future SOC Lab
(2015)
Das Future SOC Lab am HPI ist eine Kooperation des Hasso-Plattner-Instituts mit verschiedenen Industriepartnern. Seine Aufgabe ist die Ermöglichung und Förderung des Austausches zwischen Forschungsgemeinschaft und Industrie.
Am Lab wird interessierten Wissenschaftlern eine Infrastruktur von neuester Hard- und Software kostenfrei für Forschungszwecke zur Verfügung gestellt. Dazu zählen teilweise noch nicht am Markt verfügbare Technologien, die im normalen Hochschulbereich in der Regel nicht zu finanzieren wären, bspw. Server mit bis zu 64 Cores und 2 TB Hauptspeicher. Diese Angebote richten sich insbesondere an Wissenschaftler in den Gebieten Informatik und Wirtschaftsinformatik. Einige der Schwerpunkte sind Cloud Computing, Parallelisierung und In-Memory Technologien.
In diesem Technischen Bericht werden die Ergebnisse der Forschungsprojekte des Jahres 2015 vorgestellt. Ausgewählte Projekte stellten ihre Ergebnisse am 15. April 2015 und 4. November 2015 im Rahmen der Future SOC Lab Tag Veranstaltungen vor.
The functionality of organic semiconductor devices crucially depends on molecular energies, namely the ionisation energy and the electron affinity. Ionisation energy and electron affinity values of thin films are, however, sensitive to film morphology and composition, making their prediction challenging. In a combined experimental and simulation study on zinc-phthalocyanine and its fluorinated derivatives, we show that changes in ionisation energy as a function of molecular orientation in neat films or mixing ratio in blends are proportional to the molecular quadrupole component along the p-p-stacking direction. We apply these findings to organic solar cells and demonstrate how the electrostatic interactions can be tuned to optimise the energy of the charge-transfer state at the donor-acceptor interface and the dissociation barrier for free charge carrier generation. The confirmation of the correlation between interfacial energies and quadrupole moments for other materials indicates its relevance for small molecules and polymers.
Background:
Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked
to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research
comprising manifold, diverse and time
‑consuming experiments, the findings can be fostered by reusing and combin‑
ing existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible
provided that the collected observations are equipped with an adequate set of metadata. So far there have been no
common standards governing phenotypic data description, which hampered data exchange and reuse.
Results:
In this paper we propose the guidelines for proper handling of the information about plant phenotyping
experiments, in terms of both the recommended content of the description and its formatting. We provide a docu‑
ment called “Minimum Information About a Plant Phenotyping Experiment”, which specifies what information about
each experiment should be given, and a Phenotyping Configuration for the ISA
‑Tab format, which allows to practically
organise this information within a dataset. We provide examples of ISA
‑Tab
‑formatted phenotypic data, and a general
description of a few systems where the recommendations have been implemented.
Conclusions:
Acceptance of the rules described in this paper by the plant phenotyping community will help to
achieve findable, accessible, interoperable and reusable data.
Measures for interoperability of phenotypic data: minimum information requirements and formatting
(2016)
Background: Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. Results: In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. Conclusions: Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.
Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m(2)/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m(2) at follow-up among those with eGFRcrea 60 mL/min/1.73m(2) or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or (LARP4B). Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.