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958 Publications visible to you, out of a total of 958
Norms of Interocular Circumpapillary Retinal Nerve Fiber Layer Thickness Differences at 768 Retinal Locations
LIFE Adult

Abstract (Expand)

Purpose: The onset and progression of optic neuropathies like glaucoma often occurs asymmetrically between the two eyes of a patient. Interocular circumpapillary retinal nerve fiber layer thickness … (cpRNFLT) differences could detect disease earlier. To apply such differences diagnostically, detailed location specific norms are necessary. Methods: Spectral-domain optical coherence tomography cpRNFLT circle scans from the population-based Leipzig Research Centre for Civilization Diseases–Adult study were selected. At each of the 768 radial scanning locations, normative interocular cpRNFLT difference distributions were calculated based on age and interocular radius difference. Results: A total of 8966 cpRNFLT scans of healthy eyes (4483 patients; 55% female; age range, 20–79 years) were selected. Global cpRNFLT average was 1.53 µm thicker in right eyes (P < 2.2 × 10–16). On 96% of the 768 locations, left minus right eye differences were significant (P < 0.05), varying between +11.6 µm (superonasal location) and −11.8 µm (nasal location). Increased age and difference in interocular scanning radii were associated with an increased mean and variance of interocular cpRNFLT difference at most retinal locations, apart from the area temporal to the inferior RNF bundle where cpRNFLT becomes more similar between eyes with age. Conclusions: We provide pointwise normative distributions of interocular cpRNFLT differences at an unprecedentedly high spatial resolution of 768 A-scans and reveal considerable location specific asymmetries as well as their associations with age and scanning radius differences between eyes. Translational Relevance: To facilitate clinical application, we implement these age- and radius-specific norms across all 768 locations in an open-source software to generate patient-specific normative color plots.

Authors: Neda Baniasadi, Franziska G. Rauscher, Dian Li, Mengyu Wang, Eun Young Choi, Hui Wang, Thomas Peschel, Kerstin Wirkner, Toralf Kirsten, Joachim Thiery, Christoph Engel, Markus Loeffler, Tobias Elze

Date Published: 3rd Aug 2020

Publication Type: Journal article

Cohort profile: The Leipzig Research Center for Civilization Diseases–Heart study (LIFE-Heart)
Genetical Statistics and Systems Biology

Abstract

Not specified

Authors: Markus Scholz, Sylvia Henger, Frank Beutner, Andrej Teren, Ronny Baber, Anja Willenberg, Uta Ceglarek, Janne Pott, Ralph Burkhardt, Joachim Thiery

Date Published: 3rd Aug 2020

Publication Type: Journal article

Genetically programmed changes in transcription of the novel progranulin regulator
Genetical Statistics and Systems Biology

Abstract (Expand)

Progranulin is a glycoprotein marking chronic inflammation in obesity and type 2 diabetes. Previous studies suggested PSRC1 (proline and serine rich coiled-coil 1) to be a target of genetic variants … associated with serum progranulin levels. We aimed to identify potentially functional variants and characterize their role in regulation of PSRC1. Phylogenetic module complexity analysis (PMCA) prioritized four polymorphisms (rs12740374, rs629301, rs660240, rs7528419) altering transcription factor binding sites with an overall score for potential regulatory function of Sall \textgreater 7.0. The effects of these variants on transcriptional activity and binding of transcription factors were tested by luciferase reporter and electrophoretic mobility shift assays (EMSA). In parallel, blood DNA promoter methylation of two regions was tested in subjects with a very high (N = 100) or a very low (N = 100) serum progranulin. Luciferase assays revealed lower activities in vectors carrying the rs629301-A compared with the C allele. Moreover, EMSA indicated a different binding pattern for the two rs629301 alleles, with an additional prominent band for the A allele, which was finally confirmed with the supershift for the Yin Yang 1 transcription factor (YY1). Subjects with high progranulin levels manifested a significantly higher mean DNA methylation (P \textless 1 \times 10-7) in one promoter region, which was in line with a significantly lower PSRC1 mRNA expression levels in blood (P = 1 \times 10-3). Consistently, rs629301-A allele was associated with lower PSRC1 mRNA expression (P \textless 1 \times 10-7). Our data suggest that the progranulin-associated variant rs629301 modifies the transcription of PSRC1 through alteration of YY1 binding capacity. DNA methylation studies further support the role of PSRC1 in regulation of progranulin serum levels. KEY MESSAGES: PSRC1 (proline and serine rich coiled-coil 1) SNPs are associated with serum progranulin levels. rs629301 regulates PSRC1 expression by affecting Yin Yang 1 transcription factor (YY1) binding. PSRC1 is also epigenetically regulated in subjects with high progranulin levels.

Authors: Maria Keller, Claudia Gebhardt, Sandra Huth, Dorit Schleinitz, Henrike Heyne, Markus Scholz, Michael Stumvoll, Yvonne Böttcher, Anke Tönjes, Peter Kovacs

Date Published: 1st Aug 2020

Publication Type: Journal article

Analysis of GPRC6A variants in different pancreatitis etiologies
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND The G-protein-coupled receptor Class C Group 6 Member A (GPRC6A) is activated by multiple ligands and is important for the regulation of calcium homeostasis. Extracellular calcium is capable …e to increase NLRP3 inflammasome activity of the innate immune system and deletion of this proinflammatory pathway mitigated pancreatitis severity in vivo. As such this pathway and the GPRC6A receptor is a reasonable candidate gene for pancreatitis. Here we investigated the prevalence of sequence variants in the GPRC6A locus in different pancreatitis aetiologies. METHODS We selected 6 tagging SNPs with the SNPinfo LD TAG SNP Selection tool and the functional relevant SNP rs6907580 for genotyping. Cohorts from Germany, further European countries and China with up to 1,124 patients and 1,999 controls were screened for single SNPs with melting curve analysis. RESULTS We identified an association of rs1606365(G) with alcoholic chronic pancreatitis in a German (odds ratio (OR) 0.76, 95% confidence interval (CI) 0.65-0.89, p = 8 \times 10-5) and a Chinese cohort (OR 0.78, 95% CI 0.64-0.96, p = 0.02). However, this association was not replicated in a combined cohort of European patients (OR 1.18, 95% CI 0.99-1.41, p = 0.07). Finally, no association was found with acute and non-alcoholic chronic pancreatitis. CONCLUSIONS Our results support a potential role of calcium sensing receptors and inflammasome activation in alcoholic chronic pancreatitis development. As the functional consequence of the associated variant is unclear, further investigations might elucidate the relevant mechanisms.

Authors: Tom Kaune, Claudia Ruffert, Nico Hesselbarth, Marko Damm, Sebastian Krug, Julian Cardinal von Widdern, Emmanuelle Masson, Jian-Min Chen, Vinciane Rebours, Louis Buscail, Claude Férec, Robert Grützmann, Rene H. M. Te Morsche, Joost Ph Drenth, Giulia Martina Cavestro, Raffaella Alessia Zuppardo, Adrian Saftoiu, Ewa Malecka-Panas, Stanislaw Głuszek, Peter Bugert, Markus M. Lerch, Matthias Sendler, Frank Ulrich Weiss, Wen-Bin Zou, Shun-Jiang Deng, Zhuan Liao, Markus Scholz, Holger Kirsten, Peter Hegyi, Heiko Witt, Patrick Michl, Heidi Griesmann, Jonas Rosendahl

Date Published: 1st Aug 2020

Publication Type: Journal article

Medical Information Extraction in the age of Deep Learning
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

OBJECTIVES: We survey recent developments in medical Information Extraction (IE) as reported in the literature from the past three years. Our focus is on the fundamental methodological paradigm shift … from standard Machine Learning (ML) techniques to Deep Neural Networks (DNNs). We describe applications of this new paradigm concentrating on two basic IE tasks, named entity recognition and relation extraction, for two selected semantic classes-diseases and drugs (or medications)-and relations between them. METHODS: For the time period from 2017 to early 2020, we searched for relevant publications from three major scientific communities: medicine and medical informatics, natural language processing, as well as neural networks and artificial intelligence. RESULTS: In the past decade, the field of Natural Language Processing (NLP) has undergone a profound methodological shift from symbolic to distributed representations based on the paradigm of Deep Learning (DL). Meanwhile, this trend is, although with some delay, also reflected in the medical NLP community. In the reporting period, overwhelming experimental evidence has been gathered, as illustrated in this survey for medical IE, that DL-based approaches outperform non-DL ones by often large margins. Still, small-sized and access-limited corpora create intrinsic problems for data-greedy DL as do special linguistic phenomena of medical sublanguages that have to be overcome by adaptive learning strategies. CONCLUSIONS: The paradigm shift from (feature-engineered) ML to DNNs changes the fundamental methodological rules of the game for medical NLP. This change is by no means restricted to medical IE but should also deeply influence other areas of medical informatics, either NLP- or non-NLP-based.

Authors: Udo Hahn, Michel Oleynik

Date Published: 1st Aug 2020

Publication Type: Journal article

What Makes a Top-Performing Precision Medicine Search Engine?
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: Jimmy Huang, Yi Chang, Xueqi Cheng, Jaap Kamps, Vanessa Murdock, Ji-Rong Wen, Yiqun Liu, Erik Faessler, Michel Oleynik, Udo Hahn

Date Published: 25th Jul 2020

Publication Type: InProceedings

Covid-19 Transmission Trajectories-Monitoring the Pandemic in the Worldwide Context.
Task Force COVID-19 Leipzig

Abstract (Expand)

The Covid-19 pandemic is developing worldwide with common dynamics but also with marked differences between regions and countries. These are not completely understood, but presumably, provide a clue … to find ways to mitigate epidemics until strategies leading to its eradication become available. We describe an iteractive monitoring tool available in the internet. It enables inspection of the dynamic state of the epidemic in 187 countries using trajectories that visualize the transmission and removal rates of the epidemic and in this way bridge epi-curve tracking with modelling approaches. Examples were provided which characterize state of epidemic in different regions of the world in terms of fast and slow growing and decaying regimes and estimate associated rate factors. The basic spread of the disease is associated with transmission between two individuals every two-three days on the average. Non-pharmaceutical interventions decrease this value to up to ten days, whereas 'complete lock down' measures are required to stop the epidemic. Comparison of trajectories revealed marked differences between the countries regarding efficiency of measures taken against the epidemic. Trajectories also reveal marked country-specific recovery and death rate dynamics. The results presented refer to the pandemic state in May to July 2020 and can serve as 'working instruction' for timely monitoring using the interactive monitoring tool as a sort of 'seismometer' for the evaluation of the state of epidemic, e.g., the possible effect of measures taken in both, lock-down and lock-up directions. Comparison of trajectories between countries and regions will support developing hypotheses and models to better understand regional differences of dynamics of Covid-19.

Authors: H. Loeffler-Wirth, M. Schmidt, H. Binder

Date Published: 20th Jul 2020

Publication Type: Journal article

Human Diseases: COVID-19

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