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9 Publications visible to you, out of a total of 9
On the Parametrization of Epidemiologic Models-Lessons from Modelling COVID-19 Epidemic.
Genetical Statistics and Systems Biology, Task Force COVID-19 Leipzig

Abstract (Expand)

Numerous prediction models of SARS-CoV-2 pandemic were proposed in the past. Unknown parameters of these models are often estimated based on observational data. However, lag in case-reporting, changing … testing policy or incompleteness of data lead to biased estimates. Moreover, parametrization is time-dependent due to changing age-structures, emerging virus variants, non-pharmaceutical interventions, and vaccination programs. To cover these aspects, we propose a principled approach to parametrize a SIR-type epidemiologic model by embedding it as a hidden layer into an input-output non-linear dynamical system (IO-NLDS). Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. This includes data issues such as known delays or biases in reporting. We estimate model parameters including their time-dependence by a Bayesian knowledge synthesis process considering parameter ranges derived from external studies as prior information. We applied this approach on a specific SIR-type model and data of Germany and Saxony demonstrating good prediction performances. Our approach can estimate and compare the relative effectiveness of non-pharmaceutical interventions and provide scenarios of the future course of the epidemic under specified conditions. It can be translated to other data sets, i.e., other countries and other SIR-type models.

Authors: Y. Kheifetz, H. Kirsten, M. Scholz

Date Published: 2nd Jul 2022

Publication Type: Journal article

Human Diseases: COVID-19

Metabolite-Investigator: an integrated user-friendly workflow for metabolomics multi-study analysis
Genetical Statistics and Systems Biology

Abstract (Expand)

Motivation Many diseases have a metabolic background, which is increasingly investigated due to improved measurement techniques allowing high-throughput assessment of metabolic features in several body … fluids. Integrating data from multiple cohorts is of high importance to obtain robust and reproducible results. However, considerable variability across studies due to differences in sampling, measurement techniques and study populations needs to be accounted for. Results We present Metabolite-Investigator, a scalable analysis workflow for quantitative metabolomics data from multiple studies. Our tool supports all aspects of data pre-processing including data integration, cleaning, transformation, batch analysis as well as multiple analysis methods including uni- and multivariable factor-metabolite associations, network analysis and factor prioritization in one or more cohorts. Moreover, it allows identifying critical interactions between cohorts and factors affecting metabolite levels and inferring a common covariate model, all via a graphical user interface. Availability and implementation We constructed Metabolite-Investigator as a free and open web-tool and stand-alone Shiny-app. It is hosted at https://apps.health-atlas.de/metabolite-investigator/, the source code is freely available at https://github.com/cfbeuchel/Metabolite-Investigator. Supplementary information Supplementary data are available at Bioinformatics online.

Authors: Carl Beuchel, Holger Kirsten, Uta Ceglarek, Markus Scholz

Date Published: 16th Nov 2020

Publication Type: Journal article

The aging human body shape.
LIFE Adult

Abstract (Expand)

Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human … populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40-80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications.

Authors: A. Frenzel, H. Binder, N. Walter, K. Wirkner, M. Loeffler, H. Loeffler-Wirth

Date Published: 29th Mar 2020

Publication Type: Not specified

Clinical and lifestyle related factors influencing whole blood metabolite levels -- A comparative analysis of three large cohorts
Genetical Statistics and Systems Biology

Abstract (Expand)

Objective Human blood metabolites are influenced by a number of lifestyle and environmental factors. Identification of these factors and the proper quantification of their relevance provides insights …s into human biological and metabolic disease processes, is key for standardized translation of metabolite biomarkers into clinical applications, and is a prerequisite for comparability of data between studies. However, so far only limited data exist from large and well-phenotyped human cohorts and current methods for analysis do not fully account for the characteristics of these data. The primary aim of this study was to identify, quantify and compare the impact of a comprehensive set of clinical and lifestyle related factors on metabolite levels in three large human cohorts. To achieve this goal, we improve current methodology by developing a principled analysis approach, which could be translated to other cohorts and metabolite panels. Methods 63 Metabolites (amino acids, acylcarnitines) were quantified by liquid chromatography tandem mass spectrometry in three cohorts (total N~=~16,222). Supported by a simulation study evaluating various analytical approaches, we developed an analysis pipeline including preprocessing, identification, and quantification of factors affecting metabolite levels. We comprehensively identified uni- and multivariable metabolite associations considering 29 environmental and clinical factors and performed metabolic pathway enrichment and network analyses. Results Inverse normal transformation of batch corrected and outlier removed metabolite levels accompanied by linear regression analysis proved to be the best suited method to deal with the metabolite data. Association analyses revealed numerous uni- and multivariable significant associations. 15 of the analyzed 29 factors explained {\textgreater}1{\%} of variance for at least one of the metabolites. Strongest factors are application of steroid hormones, reticulocytes, waist-to-hip ratio, sex, haematocrit, and age. Effect sizes of factors are comparable across studies. Conclusions We introduced a principled approach for the analysis of MS data allowing identification, and quantification of effects of clinical and lifestyle factors with metabolite levels. We detected a number of known and novel associations broadening our understanding of the regulation of the human metabolome. The large heterogeneity observed between cohorts could almost completely be explained by differences in the distribution of influencing factors emphasizing the necessity of a proper confounder analysis when interpreting metabolite associations.

Authors: Carl Beuchel, Susen Becker, Julia Dittrich, Holger Kirsten, Anke Toenjes, Michael Stumvoll, Markus Loeffler, Holger Thiele, Frank Beutner, Joachim Thiery, Uta Ceglarek, Markus Scholz

Date Published: 17th Aug 2019

Publication Type: Not specified

Breast cancer risk in BRCA1/2 mutation carriers and noncarriers under prospective intensified surveillance.
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

Comparably little is known about breast cancer (BC) risks in women from families tested negative for BRCA1/2 mutations despite an indicative family history, as opposed to BRCA1/2 mutation carriers. We … determined the age-dependent risks of first and contralateral breast cancer (FBC, CBC) both in noncarriers and carriers of BRCA1/2 mutations, who participated in an intensified breast imaging surveillance program. The study was conducted between January 1, 2005, and September 30, 2017, at 12 university centers of the German Consortium for Hereditary Breast and Ovarian Cancer. Two cohorts were prospectively followed up for incident FBC (n = 4,380; 16,398 person-years [PY], median baseline age: 39 years) and CBC (n = 2,993; 10,090 PY, median baseline age: 42 years). Cumulative FBC risk at age 60 was 61.8% (95% CI 52.8-70.9%) for BRCA1 mutation carriers, 43.2% (95% CI 32.1-56.3%) for BRCA2 mutation carriers and 15.7% (95% CI 11.9-20.4%) for noncarriers. FBC risks were significantly higher than in the general population, with incidence rate ratios of 23.9 (95% CI 18.9-29.8) for BRCA1 mutation carriers, 13.5 (95% CI 9.2-19.1) for BRCA2 mutation carriers and 4.9 (95% CI 3.8-6.3) for BRCA1/2 noncarriers. Cumulative CBC risk 10 years after FBC was 25.1% (95% CI 19.6-31.9%) for BRCA1 mutation carriers, 6.6% (95% CI 3.4-12.5%) for BRCA2 mutation carriers and 3.6% (95% CI 2.2-5.7%) for noncarriers. CBC risk in noncarriers was similar to women with unilateral BC from the general population. Further studies are needed to confirm whether less intensified surveillance is justified in women from BRCA1/2 negative families with elevated risk.

Authors: C. Engel, C. Fischer, S. Zachariae, K. Bucksch, K. Rhiem, J. Giesecke, N. Herold, B. Wappenschmidt, V. Hubbel, M. Maringa, S. Reichstein-Gnielinski, E. Hahnen, C. R. Bartram, N. Dikow, S. Schott, D. Speiser, D. Horn, E. M. Fallenberg, M. Kiechle, A. S. Quante, A. S. Vesper, T. Fehm, C. Mundhenke, N. Arnold, E. Leinert, W. Just, U. Siebers-Renelt, S. Weigel, A. Gehrig, A. Wockel, B. Schlegelberger, S. Pertschy, K. Kast, P. Wimberger, S. Briest, M. Loeffler, U. Bick, R. K. Schmutzler

Date Published: 13th May 2019

Publication Type: Not specified

Human Diseases: hereditary breast ovarian cancer syndrome

Sequential organ failure assessment score is an excellent operationalization of disease severity of adult patients with hospitalized community acquired pneumonia - results from the prospective observational PROGRESS study.
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND: CAP (Community acquired pneumonia) is frequent, with a high mortality rate and a high burden on health care systems. Development of predictive biomarkers, new therapeutic concepts, and … epidemiologic research require a valid, reproducible, and quantitative measure describing CAP severity. METHODS: Using time series data of 1532 patients enrolled in the PROGRESS study, we compared putative measures of CAP severity for their utility as an operationalization. Comparison was based on ability to correctly identify patients with an objectively severe state of disease (death or need for intensive care with at least one of the following: substantial respiratory support, treatment with catecholamines, or dialysis). We considered IDSA/ATS minor criteria, CRB-65, CURB-65, Halm criteria, qSOFA, PSI, SCAP, SIRS-Score, SMART-COP, and SOFA. RESULTS: SOFA significantly outperformed other scores in correctly identifying a severe state of disease at the day of enrollment (AUC = 0.948), mainly caused by higher discriminative power at higher score values. Runners-up were the sum of IDSA/ATS minor criteria (AUC = 0.916) and SCAP (AUC = 0.868). SOFA performed similarly well on subsequent study days (all AUC > 0.9) and across age groups. In univariate and multivariate analysis, age, sex, and pack-years significantly contributed to higher SOFA values whereas antibiosis before hospitalization predicted lower SOFA. CONCLUSIONS: SOFA score can serve as an excellent operationalization of CAP severity and is proposed as endpoint for biomarker and therapeutic studies. TRIAL REGISTRATION: clinicaltrials.gov NCT02782013 , May 25, 2016, retrospectively registered.

Authors: P. Ahnert, P. Creutz, K. Horn, F. Schwarzenberger, M. Kiehntopf, H. Hossain, M. Bauer, F. M. Brunkhorst, K. Reinhart, U. Volker, T. Chakraborty, M. Witzenrath, M. Loffler, N. Suttorp, M. Scholz

Date Published: 4th Apr 2019

Publication Type: Journal article

Human Diseases: pneumonia

Novel Anthropometry Based on 3D-Bodyscans Applied to a Large Population Based Cohort.
LIFE Adult, Genetical Statistics and Systems Biology

Abstract (Expand)

Three-dimensional (3D) whole body scanners are increasingly used as precise measuring tools for the rapid quantification of anthropometric measures in epidemiological studies. We analyzed 3D whole body … scanning data of nearly 10,000 participants of a cohort collected from the adult population of Leipzig, one of the largest cities in Eastern Germany. We present a novel approach for the systematic analysis of this data which aims at identifying distinguishable clusters of body shapes called body types. In the first step, our method aggregates body measures provided by the scanner into meta-measures, each representing one relevant dimension of the body shape. In a next step, we stratified the cohort into body types and assessed their stability and dependence on the size of the underlying cohort. Using self-organizing maps (SOM) we identified thirteen robust meta-measures and fifteen body types comprising between 1 and 18 percent of the total cohort size. Thirteen of them are virtually gender specific (six for women and seven for men) and thus reflect most abundant body shapes of women and men. Two body types include both women and men, and describe androgynous body shapes that lack typical gender specific features. The body types disentangle a large variability of body shapes enabling distinctions which go beyond the traditional indices such as body mass index, the waist-to-height ratio, the waist-to-hip ratio and the mortality-hazard ABSI-index. In a next step, we will link the identified body types with disease predispositions to study how size and shape of the human body impact health and disease.

Authors: H. Loffler-Wirth, E. Willscher, P. Ahnert, K. Wirkner, C. Engel, M. Loeffler, H. Binder

Date Published: 29th Jul 2016

Publication Type: Not specified

Human Diseases: obesity

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