Parallelogram based approach for in vivo dose estimation of genotoxic metabolites in humans with relevance to reduction of animal experiments

Motwani, Hitesh V.; Frostne, Cecilia; Törnqvist, Margareta

doi:10.1038/s41598-017-17692-5

Cited by 11 publications

(4 citation statements)

References 40 publications

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“…As mentioned, systems biology modelling and parallelogram89 90 extrapolation are supposed to deliver small sets of highly informative features, by contributing features that are dominating model behaviour or that are shown to translate from the SASKit animal model data. Given the comparatively small number of study participants (but in-depth measurements), we also wish to explore ‘transfer learning’, which aims to utilise large amounts of public knowledge in the form of latent variables.…”

Section: Methodsmentioning

confidence: 99%

Towards biomarkers for outcomes after pancreatic ductal adenocarcinoma and ischaemic stroke, with focus on (co)-morbidity and ageing/cellular senescence (SASKit): protocol for a prospective cohort study

et al. 2020

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IntroductionAgeing-related processes such as cellular senescence are believed to underlie the accumulation of diseases in time, causing (co)morbidity, including cancer, thromboembolism and stroke. Interfering with these processes may delay, stop or reverse morbidity. The aim of this study is to investigate the link between (co)morbidity and ageing by exploring biomarkers and molecular mechanisms of disease-triggered deterioration in patients with pancreatic ductal adenocarcinoma (PDAC) and (thromboembolic) ischaemic stroke (IS).Methods and analysisWe will recruit 50 patients with PDAC, 50 patients with (thromboembolic) IS and 50 controls at Rostock University Medical Center, Germany. We will gather routine blood data, clinical performance measurements and patient-reported outcomes at up to seven points in time, alongside in-depth transcriptomics and proteomics at two of the early time points. Aiming for clinically relevant biomarkers, the primary outcome is a composite of probable sarcopenia, clinical performance (described by ECOG Performance Status for patients with PDAC and the Modified Rankin Scale for patients with stroke) and quality of life. Further outcomes cover other aspects of morbidity such as cognitive decline and of comorbidity such as vascular or cancerous events. The data analysis is comprehensive in that it includes biostatistics and machine learning, both following standard role models and additional explorative approaches. Prognostic and predictive biomarkers for interventions addressing senescence may become available if the biomarkers that we find are specifically related to ageing/cellular senescence. Similarly, diagnostic biomarkers will be explored. Our findings will require validation in independent studies, and our dataset shall be useful to validate the findings of other studies. In some of the explorative analyses, we shall include insights from systems biology modelling as well as insights from preclinical animal models. We anticipate that our detailed study protocol and data analysis plan may also guide other biomarker exploration trials.Ethics and disseminationThe study was approved by the local ethics committee (Ethikkommission an der Medizinischen Fakultät der Universität Rostock, A2019-0174), registered at the German Clinical Trials Register (DRKS00021184), and results will be published following standard guidelines.

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Section: Methodsmentioning

confidence: 99%

Towards biomarkers for outcomes after pancreatic ductal adenocarcinoma and ischaemic stroke, with focus on (co)-morbidity and ageing/cellular senescence (SASKit): protocol for a prospective cohort study

et al. 2020

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show abstract

“…As mentioned, systems biology modelling and parallelogram 113 114 extrapolation are supposed to deliver small sets of highly informative features, by contributing features that are dominating model behaviour or that are shown to translate from the SASKIt animal model data. Given the comparatively small number of study participants (but in-depth measurements), we also wish to explore “transfer learning”, which aims to utilize large amounts of public knowledge in the form of latent variables.…”

Section: Methodsmentioning

confidence: 99%

Towards biomarkers for outcomes after pancreatic ductal adenocarcinoma and ischemic stroke, with focus on (co-)morbidity and aging / cellular senescence (SASKit): protocol for a prospective cohort study

Henze

Walter

Escobar

et al. 2020

Preprint

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Aging-related processes such as cellular senescence are believed to underlie the accumulation of diseases in time, causing (co-)morbidity, including cancer, thromboembolism and stroke. Intervening into these processes may delay, stop or reverse morbidity. To study the link between (co-)morbidity and aging, by exploring biomarkers and molecular mechanisms of disease-triggered deterioration, we will recruit 50 patients with pancreatic ductal adenocarcinoma, 50 patients with (thromboembolic) ischemic stroke and 50 controls, at Rostock University Medical Center. We will gather routine blood data, clinical performance measurements and patient-reported outcomes at up to 9 points in time, and in-depth transcriptomics & proteomics at two early time points. Aiming for clinically relevant biomarkers, the primary outcome is a composite of probable sarcopenia, clinical performance (described by ECOG Performance Status for patients with pancreatic ductal adenocarcinoma and the Modified Rankin Scale for patients with stroke) and quality of life. Further outcomes cover other aspects of morbidity such as cognitive decline, and of comorbidity such as vascular or cancerous events. The data analysis is comprehensive in that it includes biostatistics & machine learning, both following standard role models & additional explorative approaches. Predictive biomarkers for interventions addressing senescence may become available if the biomarkers that we find are predominantly related to aging / cellular senescence. Similarly, diagnostic biomarkers will be explored for their relationship to aging / cellular senescence. Our findings will require validation in independent studies, and our dataset shall be useful to validate the findings of other studies. In some of the explorative analyses, we shall include insights from systems biology modeling as well as insights from preclinical animal models. We humbly suggest that our detailed study protocol and data analysis plan may also guide other biomarker exploration trials.

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“…Reverse dosimetry is the estimation of the external dose from the biomarker level using pharmacokinetic models . Forward dosimetry (a controversial used term, e.g., refs and term which is not used uniformly) is the prediction of potentially dangerous biomarker levels in humans by using the biomarker levels in animals that lead to toxic effects …”

Section: The Interpretation Of Biomonitoring Datamentioning

confidence: 99%

“…28 Forward dosimetry (a controversial used term, e.g., refs 28 and 122 term which is not used uniformly) is the prediction of potentially dangerous biomarker levels in humans by using the biomarker levels in animals that lead to toxic effects. 123 Chemical Research in Toxicology quantitation of xenobiotics and their metabolites (exogenous metabolome) present in blood or urine (Figures 1 and 2). HRMS has more recently been used for the targeted and especially untargeted analysis of environmental and biological samples.…”

Section: ■ High-resolution Mass Spectrometry and Lifetime Internal Ex...mentioning

confidence: 99%

Is It Realistic to Propose Determination of a Lifetime Internal Exposome?

Sabbioni

Berset²,

Day³

2020

Chem. Res. Toxicol.

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Biomonitoring of xenobiotics has been performed for many years in occupational and environmental medicine. It has revealed hidden exposures and the exposure of workers could be reduced. Although most of the toxic effects of chemicals on humans were discovered in workers, the scientific community has more recently focused on environmental samples. In several countries, urinary and blood samples have been collected and analyzed for xenobiotics. Health, biochemical, and clinical parameters were measured in the biomonitoring program of the Unites States. The data were collected and evaluated as group values, comparing races, ages, and gender. The term exposome was created in order to relate chemical exposure to health effects together with the terms genome, proteome, and transcriptome. Internal exposures were mostly established with snapshot measurements, which can lead to an obvious misclassification of the individual exposures. Albumin and hemoglobin adducts of xenobiotics reflect the exposure of a larger time frame, up to 120 days. It is likely that only a small fraction of xenobiotics form such adducts. In addition, adduct analyses are more work intensive than the measurement of xenobiotics and metabolites in urine and/or blood. New technology, such as high-resolution mass spectrometry, will enable the discovery of new compounds that have been overlooked in the past, since over 300,000 chemicals are commercially available and most likely also present in the environment. Yet, quantification will be challenging, as it was for the older methods. At this stage, determination of a lifetime internal exposome is very unrealistic. Instead of an experimental approach with a large number of people, which is economically and scientifically not feasible, in silico methods should be developed further to predict exposure, toxicity, and potential health effects of mixtures. The computer models will help to focus internal exposure investigations on smaller groups of people and smaller number of chemicals.

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Parallelogram based approach for in vivo dose estimation of genotoxic metabolites in humans with relevance to reduction of animal experiments

Cited by 11 publications

References 40 publications

Towards biomarkers for outcomes after pancreatic ductal adenocarcinoma and ischaemic stroke, with focus on (co)-morbidity and ageing/cellular senescence (SASKit): protocol for a prospective cohort study

Towards biomarkers for outcomes after pancreatic ductal adenocarcinoma and ischaemic stroke, with focus on (co)-morbidity and ageing/cellular senescence (SASKit): protocol for a prospective cohort study

Towards biomarkers for outcomes after pancreatic ductal adenocarcinoma and ischemic stroke, with focus on (co-)morbidity and aging / cellular senescence (SASKit): protocol for a prospective cohort study

Is It Realistic to Propose Determination of a Lifetime Internal Exposome?

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