University of Düsseldorf

About: University of Düsseldorf is a education organization based out in Düsseldorf, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 25225 authors who have published 49155 publications receiving 1946434 citations.

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.

Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).

Evolutionary analysis of Arabidopsis, cyanobacterial, and chloroplast genomes reveals plastid phylogeny and thousands of cyanobacterial genes in the nucleus.

Abstract: Chloroplasts were once free-living cyanobacteria that became endosymbionts, but the genomes of contemporary plastids encode only ≈5–10% as many genes as those of their free-living cousins, indicating that many genes were either lost from plastids or transferred to the nucleus during the course of plant evolution. Previous estimates have suggested that between 800 and perhaps as many as 2,000 genes in the Arabidopsis genome might come from cyanobacteria, but genome-wide phylogenetic surveys that could provide direct estimates of this number are lacking. We compared 24,990 proteins encoded in the Arabidopsis genome to the proteins from three cyanobacterial genomes, 16 other prokaryotic reference genomes, and yeast. Of 9,368 Arabidopsis proteins sufficiently conserved for primary sequence comparison, 866 detected homologues only among cyanobacteria and 834 other branched with cyanobacterial homologues in phylogenetic trees. Extrapolating from these conserved proteins to the whole genome, the data suggest that ≈4,500 of Arabidopsis protein-coding genes (≈18% of the total) were acquired from the cyanobacterial ancestor of plastids. These proteins encompass all functional classes, and the majority of them are targeted to cell compartments other than the chloroplast. Analysis of 15 sequenced chloroplast genomes revealed 117 nuclear-encoded proteins that are also still present in at least one chloroplast genome. A phylogeny of chloroplast genomes inferred from 41 proteins and 8,303 amino acids sites indicates that at least two independent secondary endosymbiotic events have occurred involving red algae and that amino acid composition bias in chloroplast proteins strongly affects plastid genome phylogeny.

Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps

Abstract: Probabilistic maps of neocortical areas and subcortical fiber tracts, warped to a common reference brain, have been published using microscopic architectonic parcellations in ten human postmortem brains. The maps have been successfully applied as topographical references for the anatomical localization of activations observed in functional imaging studies. Here, for the first time, we present stereotaxic, probabilistic maps of the hippocampus, the amygdala and the entorhinal cortex and some of their subdivisions. Cytoarchitectonic mapping was performed in serial, cell-body stained histological sections. The positions and the extent of cytoarchitectonically defined structures were traced in digitized histological sections, 3-D reconstructed and warped to the reference space of the MNI single subject brain using both linear and non-linear elastic tools of alignment. The probability maps and volumes of all structures were calculated. The precise localization of the borders of the mapped regions cannot be predicted consistently by macroanatomical landmarks. Many borders, e.g. between the subiculum and entorhinal cortex, subiculum and Cornu ammonis, and amygdala and hippocampus, do not match sulcal landmarks such as the bottom of a sulcus. Only microscopic observation enables the precise localization of the borders of these brain regions. The superposition of the cytoarchitectonic maps in the common spatial reference system shows a considerably lower degree of intersubject variability in size and position of the allocortical structures and nuclei than the previously delineated neocortical areas. For the first time, the present observations provide cytoarchitectonically verified maps of the human amygdala, hippocampus and entorhinal cortex, which take into account the stereotaxic position of the brain structures as well as intersubject variability. We believe that these maps are efficient tools for the precise microstructural localization of fMRI, PET and anatomical MR data, both in healthy and pathologically altered brains.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Identification and classification of hubs in brain networks.

Abstract: Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.