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  1. Article ; Online: Bayesian network modeling of risk and prodromal markers of Parkinson's disease.

    Meemansa Sood / Ulrike Suenkel / Anna-Katharina von Thaler / Helena U Zacharias / Kathrin Brockmann / Gerhard W Eschweiler / Walter Maetzler / Daniela Berg / Holger Fröhlich / Sebastian Heinzel

    PLoS ONE, Vol 18, Iss 2, p e

    2023  Volume 0280609

    Abstract: Parkinson's disease (PD) is characterized by a long prodromal phase with a multitude of markers indicating an increased PD risk prior to clinical diagnosis based on motor symptoms. Current PD prediction models do not consider interdependencies of single ... ...

    Abstract Parkinson's disease (PD) is characterized by a long prodromal phase with a multitude of markers indicating an increased PD risk prior to clinical diagnosis based on motor symptoms. Current PD prediction models do not consider interdependencies of single predictors, lack differentiation by subtypes of prodromal PD, and may be limited and potentially biased by confounding factors, unspecific assessment methods and restricted access to comprehensive marker data of prospective cohorts. We used prospective data of 18 established risk and prodromal markers of PD in 1178 healthy, PD-free individuals and 24 incident PD cases collected longitudinally in the Tübingen evaluation of Risk factors for Early detection of NeuroDegeneration (TREND) study at 4 visits over up to 10 years. We employed artificial intelligence (AI) to learn and quantify PD marker interdependencies via a Bayesian network (BN) with probabilistic confidence estimation using bootstrapping. The BN was employed to generate a synthetic cohort and individual marker profiles. Robust interdependencies were observed for BN edges from age to subthreshold parkinsonism and urinary dysfunction, sex to substantia nigra hyperechogenicity, depression, non-smoking and to constipation; depression to symptomatic hypotension and excessive daytime somnolence; solvent exposure to cognitive deficits and to physical inactivity; and non-smoking to physical inactivity. Conversion to PD was interdependent with prior subthreshold parkinsonism, sex and substantia nigra hyperechogenicity. Several additional interdependencies with lower probabilistic confidence were identified. Synthetic subjects generated via the BN based representation of the TREND study were realistic as assessed through multiple comparison approaches of real and synthetic data. Altogether our work demonstrates the potential of modern AI approaches (specifically BNs) both for modelling and understanding interdependencies between PD risk and prodromal markers, which are so far not accounted for in PD prediction ...
    Keywords Medicine ; R ; Science ; Q
    Subject code 310
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Expectation of clinical decision support systems

    Fruzsina Kotsis / Helena Bächle / Michael Altenbuchinger / Jürgen Dönitz / Yacoub Abelard Njipouombe Nsangou / Heike Meiselbach / Robin Kosch / Sabine Salloch / Tanja Bratan / Helena U. Zacharias / Ulla T. Schultheiss

    BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-

    a survey study among nephrologist end-users

    2023  Volume 12

    Abstract: Abstract Background Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are ... ...

    Abstract Abstract Background Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce. Purpose Nephrologists’ attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists’ experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting. Methods The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted. Results The study population comprised 54 physicians, with a response rate of about 80–100% per question. Most participants were aged between 51–60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction ...
    Keywords Survey ; CDSS ; Clinical Decision Support Systems ; Nephrology ; Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 310
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Vitamin D moderates the interaction between 5-HTTLPR and childhood abuse in depressive disorders

    Sarah Bonk / Johannes Hertel / Helena U. Zacharias / Jan Terock / Deborah Janowitz / Georg Homuth / Matthias Nauck / Henry Völzke / Henriette Meyer zu Schwabedissen / Sandra Van der Auwera / Hans Jörgen Grabe

    Scientific Reports, Vol 10, Iss 1, Pp 1-

    2020  Volume 9

    Abstract: Abstract A complex interplay between genetic and environmental factors determines the individual risk of depressive disorders. Vitamin D has been shown to stimulate the expression of the tryptophan hydroxylase 2 (TPH2) gene, which is the rate-limiting ... ...

    Abstract Abstract A complex interplay between genetic and environmental factors determines the individual risk of depressive disorders. Vitamin D has been shown to stimulate the expression of the tryptophan hydroxylase 2 (TPH2) gene, which is the rate-limiting enzyme for serotonin production in the brain. Therefore, we investigate the hypothesis that serum vitamin D levels moderate the interaction between the serotonin transporter promotor gene polymorphism (5-HTTLPR) and childhood abuse in depressive disorders. Two independent samples from the Study of Health in Pomerania (SHIP-LEGEND: n = 1 997; SHIP-TREND-0: n = 2 939) were used. Depressive disorders were assessed using questionnaires (BDI-II, PHQ-9) and interview procedures (DSM-IV). Besides serum vitamin D levels (25(OH)D), a functional polymorphism (rs4588) of the vitamin D-binding protein is used as a proxy for 25(OH)D. S-allele carriers with childhood abuse and low 25(OH)D levels have a higher mean BDI-II score (13.25) than those with a higher 25(OH)D level (9.56), which was not observed in abused LL-carriers. This significant three-way interaction was replicated in individuals with lifetime major depressive disorders when using the rs4588 instead of 25(OH)D (p = 0.0076 in the combined sample). We conclude that vitamin D relevantly moderates the interaction between childhood abuse and the serotonergic system, thereby impacting vulnerability to depressive disorders.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2020-12-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: A multi-source data integration approach reveals novel associations between metabolites and renal outcomes in the German Chronic Kidney Disease study

    Michael Altenbuchinger / Helena U. Zacharias / Stefan Solbrig / Andreas Schäfer / Mustafa Büyüközkan / Ulla T. Schultheiß / Fruzsina Kotsis / Anna Köttgen / Rainer Spang / Peter J. Oefner / Jan Krumsiek / Wolfram Gronwald

    Scientific Reports, Vol 9, Iss 1, Pp 1-

    2019  Volume 13

    Abstract: Abstract Omics data facilitate the gain of novel insights into the pathophysiology of diseases and, consequently, their diagnosis, treatment, and prevention. To this end, omics data are integrated with other data types, e.g., clinical, phenotypic, and ... ...

    Abstract Abstract Omics data facilitate the gain of novel insights into the pathophysiology of diseases and, consequently, their diagnosis, treatment, and prevention. To this end, omics data are integrated with other data types, e.g., clinical, phenotypic, and demographic parameters of categorical or continuous nature. We exemplify this data integration issue for a chronic kidney disease (CKD) study, comprising complex clinical, demographic, and one-dimensional 1H nuclear magnetic resonance metabolic variables. Routine analysis screens for associations of single metabolic features with clinical parameters while accounting for confounders typically chosen by expert knowledge. This knowledge can be incomplete or unavailable. We introduce a framework for data integration that intrinsically adjusts for confounding variables. We give its mathematical and algorithmic foundation, provide a state-of-the-art implementation, and evaluate its performance by sanity checks and predictive performance assessment on independent test data. Particularly, we show that discovered associations remain significant after variable adjustment based on expert knowledge. In contrast, we illustrate that associations discovered in routine univariate screening approaches can be biased by incorrect or incomplete expert knowledge. Our data integration approach reveals important associations between CKD comorbidities and metabolites, including novel associations of the plasma metabolite trimethylamine-N-oxide with cardiac arrhythmia and infarction in CKD stage 3 patients.
    Keywords Medicine ; R ; Science ; Q
    Subject code 004
    Language English
    Publishing date 2019-09-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Visceral adipose tissue but not subcutaneous adipose tissue is associated with urine and serum metabolites.

    Inga Schlecht / Wolfram Gronwald / Gundula Behrens / Sebastian E Baumeister / Johannes Hertel / Jochen Hochrein / Helena U Zacharias / Beate Fischer / Peter J Oefner / Michael F Leitzmann

    PLoS ONE, Vol 12, Iss 4, p e

    2017  Volume 0175133

    Abstract: Obesity is a complex multifactorial phenotype that influences several metabolic pathways. Yet, few studies have examined the relations of different body fat compartments to urinary and serum metabolites. Anthropometric phenotypes (visceral adipose tissue ...

    Abstract Obesity is a complex multifactorial phenotype that influences several metabolic pathways. Yet, few studies have examined the relations of different body fat compartments to urinary and serum metabolites. Anthropometric phenotypes (visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), the ratio between VAT and SAT (VSR), body mass index (BMI), waist circumference (WC)) and urinary and serum metabolite concentrations measured by nuclear magnetic resonance spectroscopy were measured in a population-based sample of 228 healthy adults. Multivariable linear and logistic regression models, corrected for multiple testing using the false discovery rate, were used to associate anthropometric phenotypes with metabolites. We adjusted for potential confounding variables: age, sex, smoking, physical activity, menopausal status, estimated glomerular filtration rate (eGFR), urinary glucose, and fasting status. In a fully adjusted logistic regression model dichotomized for the absence or presence of quantifiable metabolite amounts, VAT, BMI and WC were inversely related to urinary choline (ß = -0.18, p = 2.73*10-3), glycolic acid (ß = -0.20, 0.02), and guanidinoacetic acid (ß = -0.12, p = 0.04), and positively related to ethanolamine (ß = 0.18, p = 0.02) and dimethylamine (ß = 0.32, p = 0.02). BMI and WC were additionally inversely related to urinary glutamine and lactic acid. Moreover, WC was inversely associated with the detection of serine. VAT, but none of the other anthropometric parameters, was related to serum essential amino acids, such as valine, isoleucine, and phenylalanine among men. Compared to other adiposity measures, VAT demonstrated the strongest and most significant relations to urinary and serum metabolites. The distinct relations of VAT, SAT, VSR, BMI, and WC to metabolites emphasize the importance of accurately differentiating between body fat compartments when evaluating the potential role of metabolic regulation in the development of obesity-related diseases, such as insulin resistance, type 2 diabetes, and cardiovascular disease.
    Keywords Medicine ; R ; Science ; Q
    Subject code 630
    Language English
    Publishing date 2017-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Visceral adipose tissue but not subcutaneous adipose tissue is associated with urine and serum metabolites.

    Inga Schlecht / Wolfram Gronwald / Gundula Behrens / Sebastian E Baumeister / Johannes Hertel / Jochen Hochrein / Helena U Zacharias / Beate Fischer / Peter J Oefner / Michael F Leitzmann

    PLoS ONE, Vol 12, Iss 4, p e

    2017  Volume 0175133

    Abstract: Obesity is a complex multifactorial phenotype that influences several metabolic pathways. Yet, few studies have examined the relations of different body fat compartments to urinary and serum metabolites. Anthropometric phenotypes (visceral adipose tissue ...

    Abstract Obesity is a complex multifactorial phenotype that influences several metabolic pathways. Yet, few studies have examined the relations of different body fat compartments to urinary and serum metabolites. Anthropometric phenotypes (visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), the ratio between VAT and SAT (VSR), body mass index (BMI), waist circumference (WC)) and urinary and serum metabolite concentrations measured by nuclear magnetic resonance spectroscopy were measured in a population-based sample of 228 healthy adults. Multivariable linear and logistic regression models, corrected for multiple testing using the false discovery rate, were used to associate anthropometric phenotypes with metabolites. We adjusted for potential confounding variables: age, sex, smoking, physical activity, menopausal status, estimated glomerular filtration rate (eGFR), urinary glucose, and fasting status. In a fully adjusted logistic regression model dichotomized for the absence or presence of quantifiable metabolite amounts, VAT, BMI and WC were inversely related to urinary choline (ß = -0.18, p = 2.73*10-3), glycolic acid (ß = -0.20, 0.02), and guanidinoacetic acid (ß = -0.12, p = 0.04), and positively related to ethanolamine (ß = 0.18, p = 0.02) and dimethylamine (ß = 0.32, p = 0.02). BMI and WC were additionally inversely related to urinary glutamine and lactic acid. Moreover, WC was inversely associated with the detection of serine. VAT, but none of the other anthropometric parameters, was related to serum essential amino acids, such as valine, isoleucine, and phenylalanine among men. Compared to other adiposity measures, VAT demonstrated the strongest and most significant relations to urinary and serum metabolites. The distinct relations of VAT, SAT, VSR, BMI, and WC to metabolites emphasize the importance of accurately differentiating between body fat compartments when evaluating the potential role of metabolic regulation in the development of obesity-related diseases, such as insulin resistance, type 2 diabetes, and cardiovascular disease.
    Keywords Medicine ; R ; Science ; Q
    Subject code 630
    Language English
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: Evaluation of dilution and normalization strategies to correct for urinary output in HPLC-HRTOFMS metabolomics

    Vogl, Franziska C / Sebastian Mehrl / Leonhard Heizinger / Inga Schlecht / Helena U. Zacharias / Lisa Ellmann / Nadine Nürnberger / Wolfram Gronwald / Michael F. Leitzmann / Jerome Rossert / Kai-Uwe Eckardt / Katja Dettmer / Peter J. Oefner

    Analytical and bioanalytical chemistry. 2016 Nov., v. 408, no. 29

    2016  

    Abstract: Reliable identification of features distinguishing biological groups of interest in urinary metabolite fingerprints requires the control of total metabolite abundance, which may vary significantly as the kidneys adjust the excretion of water and solutes ... ...

    Institution GCKD Study Investigators
    Abstract Reliable identification of features distinguishing biological groups of interest in urinary metabolite fingerprints requires the control of total metabolite abundance, which may vary significantly as the kidneys adjust the excretion of water and solutes to meet the homeostatic needs of the body. Failure to account for such variation may lead to misclassification and accumulation of missing data in case of less concentrated urine specimens. Here, different pre- and post-acquisition methods of normalization were compared systematically for their ability to recover features from liquid chromatography-mass spectrometry metabolite fingerprints of urine that allow distinction between patients with chronic kidney disease and healthy controls. Methods of normalization that were employed prior to analysis included dilution of urine specimens to either a fixed creatinine concentration or osmolality value. Post-acquisition normalization methods applied to chromatograms of 1:4 diluted urine specimens comprised normalization to creatinine, osmolality, and sum of all integrals. Dilution of urine specimens to a fixed creatinine concentration resulted not only in the least number of missing values, but it was also the only method allowing the unambiguous classification of urine specimens from healthy and diseased individuals. The robustness of classification could be confirmed for two independent patient cohorts of chronic kidney disease patients and yielded a shared set of 49 discriminant metabolite features. Graphical Abstract Dilution to a uniform creatinine concentration across urine specimens yields more comparable urinary metabolite fingerprints
    Keywords creatinine ; excretion ; kidney diseases ; kidneys ; liquid chromatography ; mass spectrometry ; metabolites ; metabolomics ; osmolality ; patients ; solutes ; urine
    Language English
    Dates of publication 2016-11
    Size p. 8483-8493.
    Publishing place Springer Berlin Heidelberg
    Document type Article
    ISSN 1618-2642
    DOI 10.1007/s00216-016-9974-1
    Database NAL-Catalogue (AGRICOLA)

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