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Investigation of Adiposity Measures and Operational Taxonomic unit (OTU) Data Transformation Procedures in Stool Samples from a German Cohort Study Using Machine Learning Algorithms.

Microorganisms | 2020

The analysis of the gut microbiome with respect to health care prevention and diagnostic purposes is increasingly the focus of current research. We analyzed around 2000 stool samples from the KORA (Cooperative Health Research in the Region of Augsburg) cohort using high-throughput 16S rRNA gene amplicon sequencing representing a total microbial diversity of 2089 operational taxonomic units (OTUs). We evaluated the combination of three different components to assess the reflection of obesity related to microbiota profiles: (i) four prediction methods (i.e., partial least squares (PLS), support vector machine regression (SVMReg), random forest (RF), and M5Rules); (ii) five OTU data transformation approaches (i.e., no transformation, relative abundance without and with log-transformation, as well as centered and isometric log-ratio transformations); and (iii) predictions from nine measurements of obesity (i.e., body mass index, three measures of body shape, and five measures of body composition). Our results showed a substantial impact of all three components. The applications of SVMReg and PLS in combination with logarithmic data transformations resulted in considerably predictive models for waist circumference-related endpoints. These combinations were at best able to explain almost 40% of the variance in obesity measurements based on stool microbiota data (i.e., OTUs) only. A reduced loss in predictive performance was seen after sex-stratification in waist-height ratio compared to other waist-related measurements. Moreover, our analysis showed that the contribution of OTUs less prevalent and abundant is minor concerning the predictive power of our models.

Pubmed ID: 32290101 RIS Download

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KORA-gen (tool)

RRID:SCR_004510

KORA-gen is infrastructure to provide phenotypes, genotypes and biosamples for collaborative genetic epidemiological research. From all four surveys that have been conducted so far, the following biological material is on hand: genomic DNA, blood serum, blood plasma and EBV immortalized cell lines (form KORA S4 only). These have been extracted from blood samples and are stored in nitrogen tanks and -80 degrees C refrigerators. Genomic DNA from more than 18.000 adult subjects from Augsburg and the surrounding counties is available at present. So far, EBV immortalized cell lines from 1.600 participants are cultivated. To meet the manifold demands of researchers with genetic and molecular questions KORA-gen fulfills the following prerequisites for successful genetic-epidemiological research: * representative samples from the general population, * well characterized disease phenotypes and intermediate phenotypes, * information on environmental factors, * availability of genomic DNA, serum, plasma and urine, as well as EBV immortalized cell lines. In total, four population based health surveys have been conducted between 1984 and 2000 with 18000 participants in the age range of 25 to 74 years, and a biological specimen bank was established in order to enable scientists to perform epidemiologic research with respect to molecular and genetic questions. The KORA study center conducts regular follow-up investigations and has collected a wealth of information on sociodemography, general medical history, environmental factors, smoking, nutrition, alcohol consumption, and various laboratory parameters. This unique resource will be increased further by follow-up studies of the cohort. The assessment of statistical questions covers the definition of the study design and the calculation of statistical power. Furthermore, we offer assistance in data analysis. Kora-gen can be used by external partners. Interested parties can inform themselves interactively via internet about the available data and rules of access. The genotypic data base is a common resource to all partners.

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