Conducting an Epidemiologic Study and Making It FAIR: Reusable Tools and Procedures from a Population-Based Cohort Study.

Conducting large-scale epidemiologic studies requires powerful software for electronic data capture, data management, data quality assessments, and participant management. There is also an increasing need to make studies and the data collected findable, accessible, interoperable, and reusable (FAIR). However, reusable software tools from major studies, underlying such needs, are not necessarily known to other researchers. Therefore, this work gives an overview on the main tools used to conduct the internationally highly networked population-based project Study of Health in Pomerania (SHIP), as well as approaches taken to improve its FAIRness. Deep phenotyping, formalizing processes from data capture to data transfer, with a strong emphasis on cooperation and data exchange have laid the foundation for a broad scientific impact with more than 1500 published papers to date.

Monitoring and management of chronic kidney disease in ambulatory care - analysis of clinical and claims data from a population-based study.

BACKGROUND: Although chronic kidney disease (CKD) is highly prevalent in the general population, little research has been conducted on CKD management in ambulatory care. Objective was to assess management and quality of care by evaluating CKD coding in ambulatory care, patient diagnosis awareness, frequency of monitoring and whether appropriate patients are referred to nephrology. METHODS: Clinical data from the population-based cohort Study of Health in Pomerania (SHIP-START) were matched with claims data of the Association of Statutory Health Insurance Physicians. Quality of care was evaluated according international and German recommendations. RESULTS: Data from 1778 participants (56% female, mean age 59 years) were analysed. 10% had eGFR < 60 ml/min/1.73m2 (mean age 74 years), 15% had albuminuria. 21% had CKD as defined by KDIGO. 20% of these were coded and 7% self-reported having CKD. Coding increased with GFR stage (G3a 20%, G3b 61%, G4 75%, G5 100%). Serum creatinine and urinary dip stick testing were billed in the majority of all participants regardless of renal function. Testing frequency partially surpassed recommendations. Nephrology consultation was billed in few cases with stage G3b-G4. CONCLUSION: CKD coding increased with stage and was performed reliably in stages ≥ G4, while CKD awareness was low. Adherence to monitoring and referral criteria varied, depending on the applicability of monitoring criteria. For assessing quality of care, consent on monitoring, patient education, referral criteria and coordination of care needs to be established, accounting for patient related factors, including age and comorbidity. TRIAL REGISTRATION: This study was prospectively registered as DRKS00009812 in the German Clinical Trials Register (DRKS).

Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention.

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Detection of Low MAP Shedder Prevalence in Large Free-Stall Dairy Herds by Repeated Testing of Environmental Samples and Pooled Milk Samples.

An easy-to-use and affordable surveillance system is crucial for paratuberculosis control. The use of environmental samples and milk pools has been proven to be effective for the detection of Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds, but not for monitoring dairy herds certified as MAP non-suspect. We aimed to evaluate methods for the repeated testing of large dairy herds with a very low prevalence of MAP shedders, using different sets of environmental samples or pooled milk samples, collected monthly over a period of one year in 36 herds with known MAP shedder prevalence. Environmental samples were analyzed by bacterial culture and fecal PCR, and pools of 25 and 50 individual milk samples were analyzed by ELISA for MAP-specific antibodies. We estimated the cumulative sensitivity and specificity for up to twelve sampling events by adapting a Bayesian latent class model and taking into account the between- and within-test correlation. Our study revealed that at least seven repeated samplings of feces from the barn environment are necessary to achieve a sensitivity of 95% in herds with a within-herd shedder prevalence of at least 2%. The detection of herds with a prevalence of less than 2% is more challenging and, in addition to numerous repetitions, requires a combination of different samples.

Detection of Paratuberculosis in Dairy Herds by Analyzing the Scent of Feces, Alveolar Gas, and Stable Air.

Paratuberculosis is an important disease of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Early detection is crucial for successful infection control, but available diagnostic tests are still dissatisfying. Methods allowing a rapid, economic, and reliable identification of animals or herds affected by MAP are urgently required. This explorative study evaluated the potential of volatile organic compounds (VOCs) to discriminate between cattle with and without MAP infections. Headspaces above fecal samples and alveolar fractions of exhaled breath of 77 cows from eight farms with defined MAP status were analyzed in addition to stable air samples. VOCs were identified by GC-MS and quantified against reference substances. To discriminate MAP-positive from MAP-negative samples, VOC feature selection and random forest classification were performed. Classification models, generated for each biological specimen, were evaluated using repeated cross-validation. The robustness of the results was tested by predicting samples of two different sampling days. For MAP classification, the different biological matrices emitted diagnostically relevant VOCs of a unique but partly overlapping pattern (fecal headspace: 19, alveolar gas: 11, stable air: 4-5). Chemically, relevant compounds belonged to hydrocarbons, ketones, alcohols, furans, and aldehydes. Comparing the different biological specimens, VOC analysis in fecal headspace proved to be most reproducible, discriminatory, and highly predictive.

Detection of Mycobacterium avium ssp. paratuberculosis in Cultures From Fecal and Tissue Samples Using VOC Analysis and Machine Learning Tools.

Analysis of volatile organic compounds (VOCs) is a novel approach to accelerate bacterial culture diagnostics of Mycobacterium avium subsp. paratuberculosis (MAP). In the present study, cultures of fecal and tissue samples from MAP-infected and non-suspect dairy cattle and goats were explored to elucidate the effects of sample matrix and of animal species on VOC emissions during bacterial cultivation and to identify early markers for bacterial growth. The samples were processed following standard laboratory procedures, culture tubes were incubated for different time periods. Headspace volume of the tubes was sampled by needle trap-micro-extraction, and analyzed by gas chromatography-mass spectrometry. Analysis of MAP-specific VOC emissions considered potential characteristic VOC patterns. To address variation of the patterns, a flexible and robust machine learning workflow was set up, based on random forest classifiers, and comprising three steps: variable selection, parameter optimization, and classification. Only a few substances originated either from a certain matrix or could be assigned to one animal species. These additional emissions were not considered informative by the variable selection procedure. Classification accuracy of MAP-positive and negative cultures of bovine feces was 0.98 and of caprine feces 0.88, respectively. Six compounds indicating MAP presence were selected in all four settings (cattle vs. goat, feces vs. tissue): 2-Methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, heptanal, isoprene, and 2-heptanone. Classification accuracies for MAP growth-scores ranged from 0.82 for goat tissue to 0.89 for cattle feces. Misclassification occurred predominantly between related scores. Seventeen compounds indicating MAP growth were selected in all four settings, including the 6 compounds indicating MAP presence. The concentration levels of 2,3,5-trimethylfuran, 2-pentylfuran, 1-propanol, and 1-hexanol were indicative for MAP cultures before visible growth was apparent. Thus, very accurate classification of the VOC samples was achieved and the potential of VOC analysis to detect bacterial growth before colonies become visible was confirmed. These results indicate that diagnosis of paratuberculosis can be optimized by monitoring VOC emissions of bacterial cultures. Further validation studies are needed to increase the robustness of indicative VOC patterns for early MAP growth as a pre-requisite for the development of VOC-based diagnostic analysis systems.

Research paper on abiotic factors and their influence on Ixodes ricinus activity-observations over a two-year period at several tick collection sites in Germany.

Tick-borne diseases are a public health issue. To predict vector tick abundance and activity, it is necessary to understand the driving factors for these variables. In this study, the activity of Ixodes ricinus was investigated in forest and meadow habitats in Germany with a focus on abiotic factors. Ixodes ricinus adults, nymphs and larvae were caught by flagging over a period of 2 years. Microclimatic and weather conditions were recorded at the collection sites. Statistical models were applied to describe correlations between abiotic factors and tick activity in univariable and multivariable analyses. Tick activity was observed in a broad range of air temperature between 3 and 28 °C, and air humidity varied between 35 and 95%. In general, tick activity of nymphs and larvae was higher in forest habitats than that in meadows. With the exception of a single specimen of Dermacentor reticulatus, all ticks were Ixodes ricinus, most of them nymphs (63.2% in 2009 and 75.2% in 2010). For the latter, a negative binomial mixed-effects model fitted best to the observed parameters. The modelling results showed an activity optimum between 20 and 23 °C for air temperature and between 13 and 15 °C for ground temperature. In univariable analyses, the collection site, month, season, ground and air temperature were significant factors for the number of ticks caught and for all life stages. In the multivariable analysis, temperature, season and habitat turned out to be key drivers. Ixodes ricinus positive for RNA of tick-borne encephalitis virus was only found at a single sampling site. The results of this study can be used in risk assessments and to parameterise predictive models.

Potential Biological and Climatic Factors That Influence the Incidence and Persistence of Highly Pathogenic H5N1 Avian Influenza Virus in Egypt.

Highly pathogenic H5N1 avian influenza virus (A/H5N1) of clade 2.2.1 is endemic in poultry in Egypt where the highest number of human infections worldwide was reported. During the last 12 years the Egyptian A/H5N1 evolved into several genotypes. In 2007-2014 vaccinated poultry suffered from antigenic drift variants of clade 2.2.1.1 and in 2014/2015 an unprecedented upsurge of A/H5N1 clade 2.2.1.2 occurred in poultry and humans. Factors contributing to the endemicity or re-emergence of A/H5N1 in poultry in Egypt remain unclear. Here, three potential factors were studied: climatic factors (temperature, relative humidity, and wind speed), biological fitness in vitro, and pathogenicity in domestic Pekin and Muscovy ducks. Statistical analyses using negative binomial regression models indicated that ambient temperature in winter months influenced the spread of A/H5N1 in different geographic areas analyzed in this study. In vitro, at 4 and 56°C 2.2.1.1 and recent 2.2.1.2 viruses were more stable than other viruses used in this study. Further, Pekin ducks were more resistant than Muscovy ducks and the viruses were excreted for up to 2 weeks post-infection assuming a strong role as a reservoir. Taken together, ambient temperature in winter months potentially contributes to increasing outbreaks in some regions in Egypt. Heat stability of clade 2.2.1.1 and recent 2.2.1.2 viruses probably favors their persistence at elevated temperatures. Importantly, asymptomatically infected Pekin ducks may play an important role in the spread of avian and human-like A/H5N1 in Egypt. Therefore, control measures including targeted surveillance and culling of silently infected Pekin ducks should be considered.

On the information content of discrete phylogenetic characters.

Phylogenetic inference aims to reconstruct the evolutionary relationships of different species based on genetic (or other) data. Discrete characters are a particular type of data, which contain information on how the species should be grouped together. However, it has long been known that some characters contain more information than others. For instance, a character that assigns the same state to each species groups all of them together and so provides no insight into the relationships of the species considered. At the other extreme, a character that assigns a different state to each species also conveys no phylogenetic signal. In this manuscript, we study a natural combinatorial measure of the information content of an individual character and analyse properties of characters that provide the maximum phylogenetic information, particularly, the number of states such a character uses and how the different states have to be distributed among the species or taxa of the phylogenetic tree.

Natural Reassortants of Potentially Zoonotic Avian Influenza Viruses H5N1 and H9N2 from Egypt Display Distinct Pathogenic Phenotypes in Experimentally Infected Chickens and Ferrets.

The cocirculation of zoonotic highly pathogenic avian influenza virus (HPAIV) of subtype H5N1 and avian influenza virus (AIV) of subtype H9N2 among poultry in Egypt for at least 6 years should render that country a hypothetical hot spot for the emergence of reassortant, phenotypically altered viruses, yet no reassortants have been detected in Egypt. The present investigations proved that reassortants of the Egyptian H5N1 clade 2.2.1.2 virus and H9N2 virus of the G1-B lineage can be generated by coamplification in embryonated chicken eggs. Reassortants were restricted to the H5N1 subtype and acquired between two and all six of the internal segments of the H9N2 virus. Five selected plaque-purified reassortant clones expressed a broad phenotypic spectrum both in vitro and in vivo Two groups of reassortants were characterized to have retarded growth characteristics in vitro compared to the H5N1 parent virus. One clone provoked reduced mortality in inoculated chickens, although the characteristics of a highly pathogenic phenotype were retained. Enhanced zoonotic properties were not predicted for any of these clones, and this prediction was confirmed by ferret inoculation experiments: neither the H5N1 parent virus nor two selected clones induced severe clinical symptoms or were transmitted to sentinel ferrets by contact. While the emergence of reassortants of Egyptian HPAIV of subtype H5N1 with internal gene segments of cocirculating H9N2 viruses is possible in principle, the spread of such viruses is expected to be governed by their fitness to outcompete the parental viruses in the field. The eventual spread of attenuated phenotypes, however, would negatively impact syndrome surveillance on poultry farms and might foster enzootic virus circulation.IMPORTANCE Despite almost 6 years of the continuous cocirculation of highly pathogenic avian influenza virus H5N1 and avian influenza virus H9N2 in poultry in Egypt, no reassortants of the two subtypes have been reported. Here, the principal compatibility of the two subtypes is shown by forcing the reassortment between copassaged H5N1 und H9N2 viruses in embryonated chicken eggs. The resulting reassortant viruses displayed a wide range of pathogenicity including attenuated phenotypes in chickens, but did not show enhanced zoonotic propensities in the ferret model.

Strategies for the identification of disease-related patterns of volatile organic compounds: prediction of paratuberculosis in an animal model using random forests.

Modern statistical methods which were developed for pattern recognition are increasingly being used for data analysis in studies on emissions of volatile organic compounds (VOCs). With the detection of disease-related VOC profiles, novel non-invasive diagnostic tools could be developed for clinical applications. However, it is important to bear in mind that not all statistical methods are equally suitable for the investigation of VOC profiles. In particular, univariate methods are not able to discover VOC patterns as they consider each compound separately. The present study demonstrates this fact in practice. Using VOC samples from a controlled animal study on paratuberculosis, the random forest classification method was applied for pattern recognition and disease prediction. This strategy was compared with a prediction approach based on single compounds. Both methods were framed within a cross-validation procedure. A comparison of both strategies based on these VOC data reveals that random forests achieves higher sensitivities and specificities than predictions based on single compounds. Therefore, it will most likely be more fruitful to further investigate VOC patterns instead of single biomarkers for paratuberculosis. All methods used are thoroughly explained to aid the transfer to other data analyses.

Composition of the Hemagglutinin Polybasic Proteolytic Cleavage Motif Mediates Variable Virulence of H7N7 Avian Influenza Viruses.

Acquisition of a polybasic cleavage site (pCS) in the hemagglutinin (HA) is a prerequisite for the shift of low pathogenic (LP) avian influenza virus (AIV) to the highly pathogenic (HP) form in chickens. Whereas presence of a pCS is required for high pathogenicity, less is known about the effect of composition of pCS on virulence of AIV particularly H7N7. Here, we investigated the virulence of four avian H7N7 viruses after insertion of different naturally occurring pCS from two HPAIV H7N7 (designated pCSGE and pCSUK) or from H7N1 (pCSIT). In vitro, the different pCS motifs modulated viral replication and the HA cleavability independent on the HA background. However, in vivo, the level of virulence conferred by the different pCS varied significantly. Within the respective viral backgrounds viruses with pCSIT and pCSGE were more virulent than those coding for pCSUK. The latter showed also the most restricted spread in inoculated birds. Besides the pCS, other gene segments modulated virulence of these H7N7 viruses. Together, the specific composition of the pCS significantly influences virulence of H7N7 viruses. Eurasian LPAIV H7N7 may shift to high pathogenicity after acquisition of "specific" pCS motifs and/or other gene segments from HPAIV.