Publications

142 Publications visible to you, out of a total of 142

Abstract (Expand)

PURPOSE: Frontotemporal lobar degeneration (FTLD) is a common cause of early onset dementia. Behavioral variant frontotemporal dementia (bvFTD), its most common subtype, is characterized by deep alterations in behavior and personality. In 2011, new diagnostic criteria were suggested that incorporate imaging criteria into diagnostic algorithms. The study aimed at validating the potential of imaging criteria to individually predict diagnosis with machine learning algorithms. MATERIALS & METHODS: Brain atrophy was measured with structural magnetic resonance imaging (MRI) at 3 Tesla in a multi-centric cohort of 52 bvFTD patients and 52 healthy control subjects from the German FTLD Consortium's Study. Beside group comparisons, diagnosis bvFTD vs. controls was individually predicted in each subject with support vector machine classification in MRI data across the whole brain or in frontotemporal, insular regions, and basal ganglia known to be mainly affected based on recent meta-analyses. Multi-center effects were controlled for with a new method, "leave one center out" conjunction analyses, i.e. repeatedly excluding subjects from each center from the analysis. RESULTS: Group comparisons revealed atrophy in, most consistently, the frontal lobe in bvFTD beside alterations in the insula, basal ganglia and temporal lobe. Most remarkably, support vector machine classification enabled predicting diagnosis in single patients with a high accuracy of up to 84.6%, where accuracy was highest in a region-of-interest approach focusing on frontotemporal, insular regions, and basal ganglia in comparison with the whole brain approach. CONCLUSION: Our study demonstrates that MRI, a widespread imaging technology, can individually identify bvFTD with high accuracy in multi-center imaging data, paving the road to personalized diagnostic approaches in the future.

Authors: S. Meyer, K. Mueller, K. Stuke, S. Bisenius, J. Diehl-Schmid, F. Jessen, J. Kassubek, J. Kornhuber, A. C. Ludolph, J. Prudlo, A. Schneider, K. Schuemberg, I. Yakushev, M. Otto, M. L. Schroeter

Date Published: 29th Mar 2017

Publication Type: Journal article

Human Diseases: frontotemporal dementia

Abstract (Expand)

Clinical and epidemiological studies are commonly used in medical sciences. They typically collect data by using different input forms and information systems. Metadata describing input forms, database schemas and input systems are used for data integration but are typically distributed over different software tools; each uses portions of metadata, such as for loading (ETL), data presentation and analysis. In this paper, we describe an approach managing metadata centrally and consistently in a dedicated Metadata Repository (MDR). Metadata can be provided to different tools. Moreover, the MDR includes a matching component creating schema mappings as a prerequisite to integrate captured medical data. We describe the approach, the MDR infrastructure and provide algorithms for creating schema mappings. Finally, we show selected evaluation results. The MDR is fully operational and used to integrate data from a multitude of input forms and systems in the epidemiological study LIFE.

Authors: Toralf Kirsten, A. Kiel, M. Rühle, J.Wagner

Date Published: 2nd Mar 2017

Publication Type: Not specified

Abstract (Expand)

BACKGROUND: The Generalized Anxiety Disorder Scales GAD-7 and GAD-2 are instruments for the assessment of anxiety. The aims of this study are to test psychometric properties of these questionnaires, to provide normative values, and to investigate associations with sociodemographic factors, quality of life, psychological variables, and behavioral factors. METHODS: A German community sample (n=9721) with an age range of 18-80 years was surveyed using the GAD-7 and several other questionnaires. RESULTS: Confirmatory factor analyses confirmed the unidimensionality and measurement invariance of the GAD-7 across age and gender. Females were more anxious than males (mean scores: M=4.07 vs. M=3.01; effect size: d=0.33). There was no linear age trend. A total of 5.9% fulfilled the cut-off criterion of 10 and above. Anxiety was correlated with low quality of life, fatigue, low habitual optimism, physical complaints, sleep problems, low life satisfaction, low social support, low education, unemployment, and low income. Cigarette smoking and alcohol consumption were also associated with heightened anxiety, especially in women. When comparing the GAD-7 (7 items) with the ultra-short GAD-2 (2 items), the GAD-7 instrument was superior to the GAD-2 regarding several psychometric criteria. LIMITATIONS: The response rate (33%) was low. Because of the cross-sectional character of the study, causal conclusions cannot be drawn. A further limitation is the lack of a gold standard for diagnosing anxiety. CONCLUSIONS: The GAD-7 can be recommended for use in clinical research and routine.

Authors: A. Hinz, A. M. Klein, E. Brahler, H. Glaesmer, T. Luck, S. G. Riedel-Heller, K. Wirkner, A. Hilbert

Date Published: 1st Mar 2017

Publication Type: Not specified

Human Diseases: generalized anxiety disorder

Abstract (Expand)

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4.29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

Authors: F. Liem, G. Varoquaux, J. Kynast, F. Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, M. Rahim, A. Abraham, R. C. Craddock, S. Riedel-Heller, T. Luck, M. Loeffler, M. L. Schroeter, A. V. Witte, A. Villringer, D. S. Margulies

Date Published: 1st Mar 2017

Publication Type: Journal article

Abstract (Expand)

BACKGROUND: The Pittsburgh Sleep Quality Index (PSQI) is frequently used to assess sleep problems in patients. The aim of this study was to provide reference values for this questionnaire, to test psychometric properties, and to analyze associations with psychological, sociodemographic, and behavioral factors. METHODS: A German community sample comprising 9284 adult residents (aged 18-80 years) was surveyed using the PSQI and several other questionnaires. RESULTS: According to the generally accepted cut-off (PSQI > 5), 36% of the general population slept badly. Females reported significantly more sleep problems than males (mean scores: M = 5.5 vs. M = 4.4, respectively; effect size d = 0.35), but there was no linear association between age and sleep quality. Sleep problems were correlated with fatigue, quality of life (physical as well as mental), physical complaints, anxiety, and lack of optimism. Sleep quality was also strongly associated with socioeconomic status, professional situation (poorest sleep quality in unemployed people), and obesity. In addition to the results of the PSQI total score, mean scores of specific components of sleep quality were presented (sleep latency, sleep duration, and use of sleep medication). CONCLUSION: The PSQI proved to be a suitable instrument for measuring sleep quality. Gender differences, psychological factors, and obesity should be taken into account when groups of patients are compared with respect to sleep problems.

Authors: A. Hinz, H. Glaesmer, E. Brahler, M. Loffler, C. Engel, C. Enzenbach, U. Hegerl, C. Sander

Date Published: 21st Feb 2017

Publication Type: Journal article

Abstract (Expand)

Prognostic relevant pathways of leukocyte involvement in human myocardial ischemic-reperfusion injury are largely unknown. We enrolled 136 patients with ST-elevation myocardial infarction (STEMI) after primary angioplasty within 12 h after onset of symptoms. Following reperfusion, whole blood was collected within a median time interval of 20 h (interquartile range: 15-25 h) for genome-wide gene expression analysis. Subsequent CMR scans were performed using a standard protocol to determine infarct size (IS), area at risk (AAR), myocardial salvage index (MSI) and the extent of late microvascular obstruction (lateMO). We found 398 genes associated with lateMO and two genes with IS. Neither AAR, nor MSI showed significant correlations with gene expression. Genes correlating with lateMO were strongly related to several canonical pathways, including positive regulation of T-cell activation (p = 3.44 x 10(-5)), and regulation of inflammatory response (p = 1.86 x 10(-3)). Network analysis of multiple gene expression alterations associated with larger lateMO identified the following functional consequences: facilitated utilisation and decreased concentration of free fatty acid, repressed cell differentiation, enhanced phagocyte movement, increased cell death, vascular disease and compensatory vasculogenesis. In conclusion, the extent of lateMO after acute, reperfused STEMI correlated with altered activation of multiple genes related to fatty acid utilisation, lymphocyte differentiation, phagocyte mobilisation, cell survival, and vascular dysfunction.

Authors: A. Teren, H. Kirsten, F. Beutner, M. Scholz, L. M. Holdt, D. Teupser, M. Gutberlet, J. Thiery, G. Schuler, I. Eitel

Date Published: 3rd Feb 2017

Publication Type: Journal article

Human Diseases: myocardial infarction

Abstract (Expand)

The LIFE Child study is a large population-based longitudinal childhood cohort study conducted in the city of Leipzig, Germany. As a part of LIFE, a research project conducted at the Leipzig Research Center for Civilization Diseases, it aims to monitor healthy child development from birth to adulthood and to understand the development of lifestyle diseases such as obesity. The study consists of three interrelated cohorts; the birth cohort, the health cohort, and the obesity cohort. Depending on age and cohort, the comprehensive study program comprises different medical, psychological, and sociodemographic assessments as well as the collection of biological samples. Optimal data acquisition, process management, and data analysis are guaranteed by a professional team of physicians, certified study assistants, quality managers, scientists and statisticians. Due to the high popularity of the study, more than 3000 children have already participated until the end of 2015, and two-thirds of them participate continuously. The large quantity of acquired data allows LIFE Child to gain profound knowledge on the development of children growing up in the twenty-first century. This article reports the number of available and analyzable data and demonstrates the high relevance and potential of the study.

Authors: T. Poulain, R. Baber, M. Vogel, D. Pietzner, T. Kirsten, A. Jurkutat, A. Hiemisch, A. Hilbert, J. Kratzsch, J. Thiery, M. Fuchs, C. Hirsch, F. G. Rauscher, M. Loeffler, A. Korner, M. Nuchter, W. Kiess

Date Published: 2nd Feb 2017

Publication Type: Journal article

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